Update README.md

README.md

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 - text: "Responsibilities\n\nAs a Director of Engineering - Backend, your day-to-day activities will revolve around technical leadership, effective communication, and a hands-on approach to solving complex challenges, contributing to the overall success of the backend team and the company.\n\nTechnical Leadership\n\nSet the technical direction and architecture for the backend engineering team.\nArchitect scalable and resilient solutions leveraging AWS services.\nDrive the adoption of best practices in coding standards, testing, and deployment processes.\nHands on development, design, and execution as a player-coach with the backend engineering team.\n\nPeople Leadership\n\nMentor and coach engineers at all levels, providing guidance on technical and career development.\nFoster a culture of collaboration, learning, and innovation within the team.\nConduct regular 1:1s and yearly performance reviews and provide constructive feedback to support individual growth.\n\nProject Management\n\nPrioritize and allocate resources effectively to meet project deadlines and deliverables.\nCoordinate with Product, QA, and other cross-functional teams to gather requirements and ensure successful project execution.\nMonitor project progress, identify risks, and implement mitigation strategies as needed.\nDrive continuous improvement in project management processes and methodologies.\n\nSystem Architecture\n\nDesign and implement scalable and reliable backend systems using technologies like Python, Java, Docker, and Elasticsearch.\nUtilize Terraform for infrastructure as code to automate provisioning and deployment tasks on AWS.\nOptimize database performance and reliability across PostgreSQL, MySQL, and DynamoDB.\nImplement and drive CI/CD, monitoring, and alerting solutions to ensure system health and performance.\n\nTeam Collaboration\n\nCollaborate closely with frontend and other cross-functional teams to design and implement end-to-end solutions.\nConduct code reviews and provide technical guidance to ensure code quality and consistency.\nFoster a culture of knowledge sharing and continuous learning through tech talks, brown bag sessions, and workshops.\nEncourage a collaborative and inclusive work environment where diverse perspectives are valued.\n\nQuality Assurance\n\nImplement automated testing strategies to ensure the reliability and stability of backend services.\nEstablish and enforce coding standards, code reviews, and testing practices.\nWork closely with QA engineers to develop and maintain comprehensive test suites.\nContinuously monitor and improve the quality of code and systems through metrics and feedback loops.\n\nStrategic Planning\n\nCollaborate with senior leadership to align technical initiatives with business goals and objectives.\nProvide input into the product roadmap based on technical feasibility and resource constraints.\nIdentify opportunities for innovation and optimization to drive business value and competitive advantage.\n\nSkills and Experience\n\n8+ years of experience in software engineering, with a focus on backend development as an IC/Staff or Architect level role.\n4+ years of experience in a leadership or management role, preferably in a technology-driven organization\nProven track record of successfully leading and mentoring engineering teams\nAbility to prioritize and manage multiple projects and deadlines effectively\nExtensive experience with cloud technologies, particularly AWS, including designing and implementing scalable solutions\nStrong proficiency in at least one backend programming language such as Python or Java, with a deep understanding of its ecosystem and best practices\nHands-on experience with infrastructure as code tools like Terraform for managing cloud resources\nExperience with containerization and orchestration using Docker and container orchestration services\nIn-depth knowledge of database systems, including both relational (e.g., PostgreSQL, MySQL) and NoSQL (e.g., DynamoDB) databases, and their optimization\nDemonstrated expertise in implementing and maintaining continuous integration and deployment pipelines, ideally using Github Actions\nProficiency in version control systems like GitHub, including branching strategies and pull request workflows\nFamiliarity with search technologies such as Elasticsearch and query optimization techniques\nStrong problem-solving skills and the ability to make sound technical decisions in a fast-paced environment\nExcellent communication and collaboration skills, with the ability to work effectively with people and across teams and departments\nBachelors or Masters in Computer Science, Engineering or other related technical field\n\nTechnologies we use\n\nPython\nTerraform\nAWS\nJava\nDocker\nDatabases (PostgreSQL, MySQL and DynamoDB)\nGithub (and Github actions)\nElasticSearch\nGraphQL\n\nBenefits\n\nCompetitive salary\n25 paid vacation days\n8 bank holidays\n5 paid sick days\nSSP\nWork from home flexibility\nPaid parental leave\nPension program\nBike storage/shower facilities in building\nCareer growth and development opportunities\nThis position is not eligible for visa sponsorship.\n\nAxomic is an Equal Opportunity Employer. We base our employment decisions entirely on business needs, job requirements, and qualifications—we do not discriminate based on race, gender, religion, health, parental status, personal beliefs, veteran status, age, or any other status. We have zero tolerance for any kind of discrimination, and we are looking for candidates who share those values. Applications from women and members of underrepresented minority groups are welcomed."
   example_title: "Director of Engineering - Backend Job Description Example"
-- text: "We need a machine learning engineer to work in our growing, dynamic team. We are building internal products to help our team perform, execute and excel at their job. These tools require us to extract, analyse and infer knowledge from our content which help to inform and shape our future content pipeline.\n\nWe are looking for an entrepreneurial mindset to optimise our company’s internal and external performance using machine learning capabilities and tooling. This will span from building tooling for our teams’ workflows to predictive analytics on our vast amounts of video data.\n\nYou must be organised to ensure deadlines are met, and willing to take on new challenges. Our work is seen by millions of people each day all around the world, so your work will have a massive impact.\n\nYou should be looking for more than just a job. You should aspire to lead and own a media company one day as this position holds massive future potential for growth.\n\nAs a machine learning engineer, your role will involve:\n\nExploring and analysing our data to identify trends and predictive models that will optimise our video’s performance;\nBuilding Interactive Dashboards for Data Visualisation and Analysis.;\nFine-tuning large language models (e.g. GPT 4), and working with our script writers to help us automate parts of our content generation pipeline;\nWorking with our team to proactively suggest ways in which technology can be applied intelligently to our work pipeline;\n\nIdeal candidates should demonstrate:\n\nCreative problem-solving skills, be open-minded and willing to collaborate with developers and other members of staff.\nCommunication skills to explain complicated solutions to all levels within a business.\nA self-starter attitude with a diverse array of interests and a thirst for knowledge\nA creative spark with a proven ability to think outside of the box\n\nYou MUST have the following skills:\n\nPrevious experience in building machine learning solutions in a commercial setting\nThorough knowledge of implementing supervised and unsupervised machine learning techniques\nProduction level Python, including building backends and command line tools\nAn enthusiasm for creating and optimising digital media\nQuantitative degree from a top university\n\nThe following is DESIRABLE, not essential:\n\nCandidates with previous experience with LLM models\nCommercial Experience with Tensorflow / Keras\nDeveloping cloud native systems\nAn enthusiasm for data visualisation and dashboarding\n\nBenefits:\n\nMaking a serious impact from day one. We're an agile company at the forefront of digital content consumption, and your work will impact millions of people per day.\nA great office located in Shoreditch right by Old Street Roundabout.\nCompetitive salary based on skills and experience\n5 days per week, 9am-6pm with performance-related bonuses\nSocial office environment located right by silicon roundabout. Dog friendly, with free coffee/tea and regularly scheduled events with other companies sharing our building.\nSignificant opportunities for growth. We are looking for a senior developer to become a key and pivotal part of our team, ample to grow this segment of our company and lead others in the future.\n\nJob Types: Full-time, Permanent\n\nPay: From £80,000.00 per year\n\nBenefits:\n\nCasual dress\nCompany events\nCompany pension\nCycle to work scheme\nWork from home\n\nSchedule:\n\n8 hour shift\nFlexitime\nMonday to Friday\nOvertime\n\nSupplemental pay types:\n\nBonus scheme\nPerformance bonus\n\nEducation:\n\nBachelor's (preferred)\n\nWork authorisation:\n\nUnited Kingdom (required)\n\nAbility to Commute:\n\nLondon (required)\n\nAbility to Relocate:\n\nLondon: Relocate before starting work (required)\n\nWork Location: Hybrid remote in London"
-  example_title: "Machine Learning Engineer Job Description Example"
 - text: "The Role\n\nNesta's Data Science Practice is looking for a Product and Machine Learning (ML) Engineer to join our team. Working closely with Nesta's Data Science, Software Engineering and Design and Technology teams, the Product and ML Engineer will play a key role in increasing the impact of data science across Nesta’s 3 missions and BIT, through developing tools, models and data into scalable products. This role may suit data scientists with strong engineering skills or engineers with a strong machine learning background.\n\nKey Responsibilities:\n\nProduct development: conceiving, developing, deploying and testing data science driven products, including working as part of a multidisciplinary team to achieve this.\nInfrastructure development: collaborating with data scientists, data engineers and software engineers to create the tools, frameworks and infrastructure that enables the acceleration of ML/data driven product delivery.\nOpportunity spotting: identifying areas across the organisation that would benefit from data science enabled products, and designing solutions to achieve impact.\nScaling up algorithms: building robust, reproducible pipelines, including model training, deployment and maintenance.\nCollaboration: Work closely with data scientists, data engineers, analysts and other stakeholders to integrate cutting-edge tools and techniques to improve the scale and robustness of their work.\nCommunication: Understand and articulate trade-offs between different solutions and discuss these with relevant stakeholders to decide pragmatically between a range of options, taking into account factors such as quality, timeliness and impact.\nStandards: taking an active part in establishing ML standards and driving quality across our digital and data estate, whilst also coaching and upskilling relevant technical staff across the organisation to achieve them.\nContinuous improvement: Stay updated with the latest trends in ML engineering to drive the evolution of our platforms.\nMust-Have Skills:\n\nA minimum of 3 years working in a related technical role (e.g. Data Scientist, Data Engineer, Software Developer)\nExperience implementing and deploying machine learning models to be part of digital products or research processes.\nComfortable working with several machine learning frameworks (such as PyTorch, scikit-learn, huggingface, spaCy)\nAbility to write code with testability, readability, edge cases and errors in mind\nAn understanding of software development lifecycles (e.g. system design, MLOps architecture)\nFamiliarity with engineering and DevOps practices (e.g. CI/CD, containerisation)\nSolid understanding of cloud services and systems.\nVersion control using Git/Github or equivalent.\nAbility to convert complex data requirements into scalable solutions meeting user/stakeholder needs.\nStrong communication skills and proven experience collaborating with a diverse range of stakeholders, including non-technical collaborators.\nExperience with agile methodologies and rapid iteration - you have experience of iteratively developing software solutions and know when to use ML or other approaches to demonstrate user and stakeholder value.\nNice-to-Haves:\n\nPrevious experience in a research or data-intensive environment.\nPrevious experience working in a product focused software development environment\nPrevious experience developing LLM driven solutions/applications\nEvidence of developing/contributing to open source software\nExperience of working in the public or third sector, or a start-up environment."
   example_title: "Product and Machine Learning Engineer Job Description Example"
+- text: "We need a machine learning engineer to work in our growing, dynamic team. We are building internal products to help our team perform, execute and excel at their job. These tools require us to extract, analyse and infer knowledge from our content which help to inform and shape our future content pipeline.\n\nWe are looking for an entrepreneurial mindset to optimise our company’s internal and external performance using machine learning capabilities and tooling. This will span from building tooling for our teams’ workflows to predictive analytics on our vast amounts of video data.\n\nYou must be organised to ensure deadlines are met, and willing to take on new challenges. Our work is seen by millions of people each day all around the world, so your work will have a massive impact.\n\nYou should be looking for more than just a job. You should aspire to lead and own a media company one day as this position holds massive future potential for growth.\n\nAs a machine learning engineer, your role will involve:\n\nExploring and analysing our data to identify trends and predictive models that will optimise our video’s performance;\nBuilding Interactive Dashboards for Data Visualisation and Analysis.;\nFine-tuning large language models (e.g. GPT 4), and working with our script writers to help us automate parts of our content generation pipeline;\nWorking with our team to proactively suggest ways in which technology can be applied intelligently to our work pipeline;\n\nIdeal candidates should demonstrate:\n\nCreative problem-solving skills, be open-minded and willing to collaborate with developers and other members of staff.\nCommunication skills to explain complicated solutions to all levels within a business.\nA self-starter attitude with a diverse array of interests and a thirst for knowledge\nA creative spark with a proven ability to think outside of the box\n\nYou MUST have the following skills:\n\nPrevious experience in building machine learning solutions in a commercial setting\nThorough knowledge of implementing supervised and unsupervised machine learning techniques\nProduction level Python, including building backends and command line tools\nAn enthusiasm for creating and optimising digital media\nQuantitative degree from a top university\n\nThe following is DESIRABLE, not essential:\n\nCandidates with previous experience with LLM models\nCommercial Experience with Tensorflow / Keras\nDeveloping cloud native systems\nAn enthusiasm for data visualisation and dashboarding\n\nBenefits:\n\nMaking a serious impact from day one. We're an agile company at the forefront of digital content consumption, and your work will impact millions of people per day.\nA great office located in Shoreditch right by Old Street Roundabout.\nCompetitive salary based on skills and experience\n5 days per week, 9am-6pm with performance-related bonuses\nSocial office environment located right by silicon roundabout. Dog friendly, with free coffee/tea and regularly scheduled events with other companies sharing our building.\nSignificant opportunities for growth. We are looking for a senior developer to become a key and pivotal part of our team, ample to grow this segment of our company and lead others in the future.\n\nJob Types: Full-time, Permanent\n\nPay: From £80,000.00 per year\n\nBenefits:\n\nCasual dress\nCompany events\nCompany pension\nCycle to work scheme\nWork from home\n\nSchedule:\n\n8 hour shift\nFlexitime\nMonday to Friday\nOvertime\n\nSupplemental pay types:\n\nBonus scheme\nPerformance bonus\n\nEducation:\n\nBachelor's (preferred)\n\nWork authorisation:\n\nUnited Kingdom (required)\n\nAbility to Commute:\n\nLondon (required)\n\nAbility to Relocate:\n\nLondon: Relocate before starting work (required)\n\nWork Location: Hybrid remote in London"
+  example_title: "Machine Learning Engineer Job Description Example"
 
 language:
 - en