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tags: |
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- spacy |
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- token-classification |
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- ner |
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- named entity recognition |
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- job description named entity recognition |
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widget: |
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- text: >- |
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Responsibilities |
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As a Director of Engineering - Backend, your day-to-day activities will |
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revolve around technical leadership, effective communication, and a hands-on |
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approach to solving complex challenges, contributing to the overall success |
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of the backend team and the company. |
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Technical Leadership |
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Set the technical direction and architecture for the backend engineering |
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team. |
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Architect scalable and resilient solutions leveraging AWS services. |
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Drive the adoption of best practices in coding standards, testing, and |
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deployment processes. |
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Hands on development, design, and execution as a player-coach with the |
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backend engineering team. |
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People Leadership |
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Mentor and coach engineers at all levels, providing guidance on technical |
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and career development. |
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Foster a culture of collaboration, learning, and innovation within the team. |
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Conduct regular 1:1s and yearly performance reviews and provide constructive |
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feedback to support individual growth. |
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Project Management |
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Prioritize and allocate resources effectively to meet project deadlines and |
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deliverables. |
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Coordinate with Product, QA, and other cross-functional teams to gather |
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requirements and ensure successful project execution. |
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Monitor project progress, identify risks, and implement mitigation |
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strategies as needed. |
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Drive continuous improvement in project management processes and |
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methodologies. |
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System Architecture |
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Design and implement scalable and reliable backend systems using |
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technologies like Python, Java, Docker, and Elasticsearch. |
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Utilize Terraform for infrastructure as code to automate provisioning and |
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deployment tasks on AWS. |
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Optimize database performance and reliability across PostgreSQL, MySQL, and |
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DynamoDB. |
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Implement and drive CI/CD, monitoring, and alerting solutions to ensure |
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system health and performance. |
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Team Collaboration |
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Collaborate closely with frontend and other cross-functional teams to design |
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and implement end-to-end solutions. |
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Conduct code reviews and provide technical guidance to ensure code quality |
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and consistency. |
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Foster a culture of knowledge sharing and continuous learning through tech |
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talks, brown bag sessions, and workshops. |
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Encourage a collaborative and inclusive work environment where diverse |
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perspectives are valued. |
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Quality Assurance |
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Implement automated testing strategies to ensure the reliability and |
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stability of backend services. |
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Establish and enforce coding standards, code reviews, and testing practices. |
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Work closely with QA engineers to develop and maintain comprehensive test |
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suites. |
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Continuously monitor and improve the quality of code and systems through |
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metrics and feedback loops. |
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Strategic Planning |
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Collaborate with senior leadership to align technical initiatives with |
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business goals and objectives. |
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Provide input into the product roadmap based on technical feasibility and |
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resource constraints. |
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Identify opportunities for innovation and optimization to drive business |
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value and competitive advantage. |
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Skills and Experience |
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8+ years of experience in software engineering, with a focus on backend |
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development as an IC/Staff or Architect level role. |
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4+ years of experience in a leadership or management role, preferably in a |
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technology-driven organization |
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Proven track record of successfully leading and mentoring engineering teams |
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Ability to prioritize and manage multiple projects and deadlines effectively |
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Extensive experience with cloud technologies, particularly AWS, including |
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designing and implementing scalable solutions |
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Strong proficiency in at least one backend programming language such as |
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Python or Java, with a deep understanding of its ecosystem and best |
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practices |
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Hands-on experience with infrastructure as code tools like Terraform for |
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managing cloud resources |
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Experience with containerization and orchestration using Docker and |
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container orchestration services |
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In-depth knowledge of database systems, including both relational (e.g., |
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PostgreSQL, MySQL) and NoSQL (e.g., DynamoDB) databases, and their |
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optimization |
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Demonstrated expertise in implementing and maintaining continuous |
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integration and deployment pipelines, ideally using Github Actions |
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Proficiency in version control systems like GitHub, including branching |
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strategies and pull request workflows |
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Familiarity with search technologies such as Elasticsearch and query |
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optimization techniques |
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Strong problem-solving skills and the ability to make sound technical |
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decisions in a fast-paced environment |
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Excellent communication and collaboration skills, with the ability to work |
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effectively with people and across teams and departments |
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Bachelors or Masters in Computer Science, Engineering or other related |
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technical field |
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Technologies we use |
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Python |
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Terraform |
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AWS |
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Java |
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Docker |
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Databases (PostgreSQL, MySQL and DynamoDB) |
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Github (and Github actions) |
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ElasticSearch |
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GraphQL |
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Benefits |
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Competitive salary |
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25 paid vacation days |
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8 bank holidays |
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5 paid sick days |
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SSP |
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Work from home flexibility |
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Paid parental leave |
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Pension program |
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Bike storage/shower facilities in building |
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Career growth and development opportunities |
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This position is not eligible for visa sponsorship. |
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Axomic is an Equal Opportunity Employer. We base our employment decisions |
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entirely on business needs, job requirements, and qualifications—we do not |
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discriminate based on race, gender, religion, health, parental status, |
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personal beliefs, veteran status, age, or any other status. We have zero |
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tolerance for any kind of discrimination, and we are looking for candidates |
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who share those values. Applications from women and members of |
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underrepresented minority groups are welcomed. |
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example_title: Director of Engineering - Backend Job Description Example |
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- text: >- |
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The Role |
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Nesta's Data Science Practice is looking for a Product and Machine Learning |
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(ML) Engineer to join our team. Working closely with Nesta's Data Science, |
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Software Engineering and Design and Technology teams, the Product and ML |
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Engineer will play a key role in increasing the impact of data science |
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across Nesta’s 3 missions and BIT, through developing tools, models and data |
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into scalable products. This role may suit data scientists with strong |
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engineering skills or engineers with a strong machine learning background. |
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Key Responsibilities: |
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Product development: conceiving, developing, deploying and testing data |
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science driven products, including working as part of a multidisciplinary |
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team to achieve this. |
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Infrastructure development: collaborating with data scientists, data |
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engineers and software engineers to create the tools, frameworks and |
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infrastructure that enables the acceleration of ML/data driven product |
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delivery. |
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Opportunity spotting: identifying areas across the organisation that would |
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benefit from data science enabled products, and designing solutions to |
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achieve impact. |
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Scaling up algorithms: building robust, reproducible pipelines, including |
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model training, deployment and maintenance. |
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Collaboration: Work closely with data scientists, data engineers, analysts |
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and other stakeholders to integrate cutting-edge tools and techniques to |
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improve the scale and robustness of their work. |
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Communication: Understand and articulate trade-offs between different |
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solutions and discuss these with relevant stakeholders to decide |
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pragmatically between a range of options, taking into account factors such |
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as quality, timeliness and impact. |
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Standards: taking an active part in establishing ML standards and driving |
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quality across our digital and data estate, whilst also coaching and |
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upskilling relevant technical staff across the organisation to achieve them. |
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Continuous improvement: Stay updated with the latest trends in ML |
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engineering to drive the evolution of our platforms. |
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Must-Have Skills: |
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A minimum of 3 years working in a related technical role (e.g. Data |
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Scientist, Data Engineer, Software Developer) |
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Experience implementing and deploying machine learning models to be part of |
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digital products or research processes. |
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Comfortable working with several machine learning frameworks (such as |
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PyTorch, scikit-learn, huggingface, spaCy) |
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Ability to write code with testability, readability, edge cases and errors |
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in mind |
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An understanding of software development lifecycles (e.g. system design, |
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MLOps architecture) |
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Familiarity with engineering and DevOps practices (e.g. CI/CD, |
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containerisation) |
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Solid understanding of cloud services and systems. |
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Version control using Git/Github or equivalent. |
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Ability to convert complex data requirements into scalable solutions meeting |
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user/stakeholder needs. |
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Strong communication skills and proven experience collaborating with a |
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diverse range of stakeholders, including non-technical collaborators. |
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Experience with agile methodologies and rapid iteration - you have |
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experience of iteratively developing software solutions and know when to use |
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ML or other approaches to demonstrate user and stakeholder value. |
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Nice-to-Haves: |
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Previous experience in a research or data-intensive environment. |
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Previous experience working in a product focused software development |
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environment |
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Previous experience developing LLM driven solutions/applications |
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Evidence of developing/contributing to open source software |
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Experience of working in the public or third sector, or a start-up |
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environment. |
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example_title: Product and Machine Learning Engineer Job Description Example |
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- text: >- |
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We need a machine learning engineer to work in our growing, dynamic team. We |
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are building internal products to help our team perform, execute and excel |
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at their job. These tools require us to extract, analyse and infer knowledge |
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from our content which help to inform and shape our future content pipeline. |
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We are looking for an entrepreneurial mindset to optimise our company’s |
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internal and external performance using machine learning capabilities and |
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tooling. This will span from building tooling for our teams’ workflows to |
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predictive analytics on our vast amounts of video data. |
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You must be organised to ensure deadlines are met, and willing to take on |
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new challenges. Our work is seen by millions of people each day all around |
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the world, so your work will have a massive impact. |
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You should be looking for more than just a job. You should aspire to lead |
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and own a media company one day as this position holds massive future |
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potential for growth. |
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As a machine learning engineer, your role will involve: |
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Exploring and analysing our data to identify trends and predictive models |
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that will optimise our video’s performance; |
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Building Interactive Dashboards for Data Visualisation and Analysis.; |
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Fine-tuning large language models (e.g. GPT 4), and working with our script |
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writers to help us automate parts of our content generation pipeline; |
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Working with our team to proactively suggest ways in which technology can be |
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applied intelligently to our work pipeline; |
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Ideal candidates should demonstrate: |
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Creative problem-solving skills, be open-minded and willing to collaborate |
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with developers and other members of staff. |
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Communication skills to explain complicated solutions to all levels within a |
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business. |
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A self-starter attitude with a diverse array of interests and a thirst for |
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knowledge |
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A creative spark with a proven ability to think outside of the box |
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You MUST have the following skills: |
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Previous experience in building machine learning solutions in a commercial |
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setting |
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Thorough knowledge of implementing supervised and unsupervised machine |
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learning techniques |
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Production level Python, including building backends and command line tools |
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An enthusiasm for creating and optimising digital media |
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Quantitative degree from a top university |
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The following is DESIRABLE, not essential: |
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Candidates with previous experience with LLM models |
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Commercial Experience with Tensorflow / Keras |
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Developing cloud native systems |
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An enthusiasm for data visualisation and dashboarding |
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Benefits: |
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Making a serious impact from day one. We're an agile company at the |
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forefront of digital content consumption, and your work will impact millions |
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of people per day. |
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A great office located in Shoreditch right by Old Street Roundabout. |
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Competitive salary based on skills and experience |
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5 days per week, 9am-6pm with performance-related bonuses |
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Social office environment located right by silicon roundabout. Dog friendly, |
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with free coffee/tea and regularly scheduled events with other companies |
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sharing our building. |
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Significant opportunities for growth. We are looking for a senior developer |
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to become a key and pivotal part of our team, ample to grow this segment of |
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our company and lead others in the future. |
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Job Types: Full-time, Permanent |
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Pay: From £80,000.00 per year |
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Benefits: |
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Casual dress |
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Company events |
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Company pension |
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Cycle to work scheme |
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Work from home |
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Schedule: |
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8 hour shift |
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Flexitime |
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Monday to Friday |
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Overtime |
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Supplemental pay types: |
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Bonus scheme |
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Performance bonus |
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Education: |
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Bachelor's (preferred) |
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Work authorisation: |
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United Kingdom (required) |
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Ability to Commute: |
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London (required) |
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Ability to Relocate: |
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London: Relocate before starting work (required) |
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Work Location: Hybrid remote in London |
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example_title: Machine Learning Engineer Job Description Example |
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language: |
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- en |
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model-index: |
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- name: en_pipeline |
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results: |
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- task: |
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name: NER |
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type: token-classification |
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metrics: |
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- name: NER Precision |
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type: precision |
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value: 0.9006239689 |
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- name: NER Recall |
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type: recall |
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value: 1 |
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- name: NER F Score |
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type: f_score |
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value: 0.9430596847 |
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library_name: spacy |
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license: afl-3.0 |
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datasets: |
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- Etietop/data_analyst_jobs |
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--- |
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| Feature | Description | |
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| --- | --- | |
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| **Name** | `en_pipeline` | |
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| **Version** | `0.0.0` | |
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| **spaCy** | `>=3.7.4,<3.8.0` | |
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| **Default Pipeline** | `tok2vec`, `ner` | |
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| **Components** | `tok2vec`, `ner` | |
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| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | |
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| **Sources** | Research at ITMO University. Dataset from Google Search Jobs | |
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| **License** | Academic Free License | |
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| **Author** | Etietop Abraham| |
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### Label Scheme |
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<details> |
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<summary>View label scheme (9 labels for 1 components)</summary> |
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| Component | Labels | |
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| --- | --- | |
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| **`ner`** | `Certifications`, `Duties and Responsibilities`, `Education`, `Experience`, `Industry`, `Job Title`, `Skills`, `Soft Skills`, `Tools and Technologies` | |
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</details> |
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### Accuracy |
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| Type | Score | |
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| `ENTS_F` | 94.31 | |
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| `ENTS_P` | 90.06 | |
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| `ENTS_R` | 100.00 | |
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| `TOK2VEC_LOSS` | 483216.60 | |
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| `NER_LOSS` | 858473.26 | |