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Software Engineer (Leadership) - Machine Learning

Faculty

<div><h2 class="jobSectionHeader">Why Faculty? 
</h2> 
We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we&rsquo;ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.
We don&rsquo;t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.
Our business, and reputation, is growing fast and we&rsquo;re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.
AI is an epoch-defining technology, join a company where you&rsquo;ll be empowered to envision its most powerful applications, and to make them happen.<div> 
</div><h2 class="jobSectionHeader">
About the team</h2><div> 
</div>Our Public Services Business Unit is committed to leveraging AI for the benefit of individual citizens and the public good. 
 
From our work informing strategic government decisions, to optimising our NHS, through to reducing bureaucratic backlogs - we know that AI offers opportunities to drive improvements at every level of Government and we are proud to lead on some of the most impactful work happening in the sector. 
 
Because of the nature of the work we do with our Government clients, you may need to be eligible for UK Security Clearance (SC) and willing to work on site with these clients from time to time.<h2 class="jobSectionHeader">
About the role</h2><div></div> 
As a Lead Data Scientist, you'll take on a pivotal, entrepreneurial role, functioning as the technical expert who thrives on complexity and commercial impact. You will be responsible for setting the technical direction and ensuring the high-quality, scalable delivery of our most challenging, high-impact projects. 
 
 
 
This position combines deep expertise in machine learning with strategic oversight to define project roadmaps, manage technical risk, and architect reliable solutions. Your focus will be on driving innovation, mentoring cross-functional teams, and actively shaping both our technical standards and long-term customer relationships.<div></div><h2 class="jobSectionHeader"> 

What you'll be doing:</h2><div></div><ul><li> 
Setting the technical direction for complex, business-critical projects and expertly balancing trade-offs between speed, innovation, and reliability.</li><li>
Designing and implementing reliable, production-grade technical solutions, ensuring comprehensive documentation of architectures and specifications.</li><li>
Defining project problems, developing clear roadmaps, and overseeing end-to-end delivery across multi-disciplinary workstreams.</li><li>
Leading technical scoping and feasibility studies for high-value sales opportunities and strategic customer engagements.</li><li>
Managing relationships and communications with demanding clients, fostering trust and aligning technical solutions with shared long-term commercial goals.</li><li>
Driving the adoption of best practices, shared resources, and robust technical processes across the wider Data Science craft.</li><li>
Mentoring and developing other data scientists and team members, actively contributing to the growth and technical excellence of the organisation.</li></ul><div> 
</div><h2 class="jobSectionHeader">
Who we're looking for:</h2><div></div><ul><li> 
You bring depth of expertise in at least one machine learning domain and strong technical breadth across the entire data science landscape.</li><li>
You are a skilled technical leader, proficient in mentoring individuals, managing teams (including other managers), and rolling out impactful tools and workflows.</li><li>
You have proven project management expertise, capable of dividing complex, ill-defined problems into actionable, clearly defined workstreams with timelines you can defend.</li><li>
You are adept at managing ill-defined, high-risk tasks, consistently delivering innovative and practical outcomes under commercial pressure.</li><li>
You possess strong customer leadership skills, able to act as a trusted technical advisor and drive long-term strategic relationships with demanding clients.</li><li>
You excel at cross-functional collaboration, effectively aligning technical strategy with Engineering, Commercial (BD), and Infrastructure teams.</li><li>
You have experience extending technical oversight to business unit-level initiatives, using your vision to influence and contribute to organisational success.</li></ul><div> 
</div><h2 class="jobSectionHeader">
Our Interview Process</h2><div></div><ul><li> 
Talent Team Screen (30 minutes)</li><li>
Introduction to the team (45 minutes)</li><li>
Technical Interview (90 minutes)
</li><li>Commercial Interview (60 minutes)</li></ul>
#LI-PRIO<h2 class="jobSectionHeader">
Our Recruitment Ethos</h2>
We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We&rsquo;re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Some of our standout benefits:<ul><li>
Unlimited Annual Leave Policy</li><li>
Private healthcare and dental</li><li>
Enhanced parental leave</li><li>
Family-Friendly Flexibility &amp; Flexible working</li><li>
Sanctus Coaching</li><li>
Hybrid Working</li></ul>
If you don&rsquo;t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.</div>

Lead Data Scientist

Penta

<div><h4 class="jobSectionHeader">What&rsquo;s in it for me?
</h4><ul><li>Competitive salary and compensation structure</li><li>
Generous paid time off and holiday schedule</li><li>
Frequent firm-wide social events and activities</li><li>
Excellent environment for learning and growth</li><li>
Further benefits, depending on location</li></ul><h4 class="jobSectionHeader"> 
About the Role</h4><div>
We are looking for a hands-on technical leader to lead Penta&rsquo;s Data Science team: someone who still designs, builds and reviews real solutions while owning execution, delivery and team development. You will be accountable for turning data science capability into shipped, dependable value for our clients and advisory teams, in alignment with our product roadmap. 
 
Penta&rsquo;s technology makes client outcomes sharper, faster, more differentiated and harder to replace. The Data Science team&rsquo;s success is measured by how much it improves live client work, not by technical elegance in isolation. 
 
Our core data science focus is natural language understanding at scale, processing millions of articles daily across stakeholder sentiment, topic identification over time, competitive peer-set selection, summarisation, contextualisation and other processing of unstructured content. Most use cases are creative chains of multiple steps drawn from data processing, exploratory analysis, fundamental ML, NLP, SQL, LLMs and integration into our live systems.</div> 

What you&rsquo;ll do 
 
Lead the team<ul><li>
Manage, coach and develop Penta&rsquo;s Data Science team, setting priorities, planning capacity and creating a high-trust, high-output delivery culture.</li><li>
Translate the product roadmap and advisory needs into a focused data science plan, partnering with Product, Advisory, Database, Development and DevOps teams to keep delivery aligned with client outcomes.</li><li>
Raise the delivery bar for execution, quality, pace, maintainability and cost discipline.</li></ul>
Ship production data science and AI systems<ul><li>
Design, build and review data science solutions across NLP, LLM workflows, machine learning, SQL and large-scale content processing.</li><li>
Own technical design and architecture for data-science-enabled applications, ensuring solutions are maintainable, supportable, observable and easy to operate.</li><li>
Productionise delivery with DevOps and MLOps, automating deployment in AWS and puttinge evaluation, monitoring and provider-routing controls in place so AI outputs remain reliable and cost-effective.</li></ul>
Scale practical AI adoption<ul><li>
Design and implement AI workflows as skills, models and MCP tools in OpenWebUI, with cost control, provider routing and observability built in.</li><li>
Partner with other departments to turn AI capabilities into everyday workflows, reusable tools and knowledge layers that improve internal productivity and client delivery.</li><li>
Evaluate emerging AI tools, models and agentic patterns, bringing the useful ones into production quickly and responsibly.</li></ul><div>
Success in this role 
 
Means the Data Science team is shipping reliable, maintainable AI and analytics capabilities into live client and advisory workflows; team members are growing; delivery is predictable; and Penta&rsquo;s applied AI capability is visibly improving across products and engagements. 
 
The Team 
 
Our Technology team supports Penta&rsquo;s ambitious delivery plans, using technology to automate solutions, optimise outcomes and support continuous integration and deployment. The six-person Data Science team sits alongside Development, Engineering / DevOps &amp; Platform Security, IT and the PMO, and works hand in hand with the Product team. 
 
The environment is collaborative, pragmatic and delivery-focused. We move quickly, share ideas openly, and use regular hackathons and experiments to generate practical business value. 
 
This is the hands-on leadership role for that team. Reporting to the CTO, You will lead a team working at the frontier of applied AI and data science, combining production LLM workflows, advanced prompting, agentic tooling, NLP, ML and large-scale content processing. You will set its direction, raise its delivery bar, grow its people through hands-on coaching, and lead from the front by actively shaping and delivering the work yourself. 
 
Our approach to AI is practical 
 
We are forward-thinking and ambitious in practically applying AI across client-facing work, corporate teams, technology and data science. We do not train our own foundation models; we apply, orchestrate and evaluate the best available models from major providers, engineering them into robust workflows that solve real business problems. 
 
We validate and document our methodologies through white papers and technical explainers, setting out the academic and analytical foundations behind our products, and the evidence that supports their use. This helps build trust in our tools, why they work and shows how they can be applied. 
 
We build on open-source AI software, including LiteLLM and OpenWebUI, to maximise the internal value of AI and build durable institutional capability. Reliability, cost control, observability, instruction-following, usability and adoption matter most. 
 
The team designs reusable workflows, skills, models and MCP tools that support Penta&rsquo;s move towards an AI-native advisory operating system. Keeping Penta at the forefront of practical AI in PR, communications and strategic consultancy is part of the role.</div><h4 class="jobSectionHeader">
About You</h4>
Tech skills required: applied AI, LLMs and data science 
<ul><li>
Advanced Python coding for data science</li><li>
Power-user fluency with frontier AI tools, especially Claude: expert-level prompting, context engineering, agentic workflows, model selection, evaluation, and practical use of the latest AI- native data science techniques</li><li>
Practical experience engineering production LLM workflows, including prompt / skill design, evaluation, cost control, provider routing, agentic / human-in-the-loop orchestration, embeddings, vector search and RAG</li><li>
Implementation of foundational ML algorithms, classic NLP techniques and LLMs</li><li>
Strong SQL for analytical and production use, ideally PostgreSQL, including complex joins, CTEs and aggregation</li><li>
AWS: EC2, ECS, S3; DevOps and automated deployment</li><li>
Git version control</li><li>
Ideally experience with OpenWebUI, LiteLLM, MCP tools and/or Claude Code</li></ul>
Key competencies &amp; experience<ul><li>
Significant hands-on experience as an Applied AI / Data Science technical leader, with recent, practical experience using frontier LLMs, prompting and agentic workflows to ship production systems. Typically this will mean around 10+ years&rsquo; hands-on experience, with technical-leadership exposure.</li><li>
A suitable degree, ideally in Software Engineering or a related technical field, and the technical grounding set out above will round out the profile.</li></ul>
The successful candidate will also have:<ul><li>
an analytical and logical mind, dynamic, positive and ready to make a difference;</li><li>
the ability to communicate complex technical topics clearly to senior, non-technical and technical audiences;</li><li>
a passionate drive for code quality, results and getting work shipped, with sound judgement on build-vs-buy, prioritisation and balancing speed against maintainability, cost and risk.</li></ul>
We strongly believe in developing talent and are willing to invest time to develop the people who join our team.<h4 class="jobSectionHeader">
About us</h4>
Penta Group is a global company providing data-driven solutions to help clients achieve their objectives in an increasingly complex stakeholder environment. We provide cutting-edge intelligence products to help clients understand what their stakeholders think, see, and hear, and then leverage that intelligence to develop and execute effective, measurable strategies. 
 
Our global team brings decades of experience in business, government, communications, research, data science, and media. Our clients include companies across a variety of industries, including technology, financial services, energy, healthcare, and more. Penta has offices in New York, London, Washington, DC, San Francisco, Dublin, London, Brussels, Singapore, and Hong Kong.</div>

VP, Head of Data Science

JPMorganChase

<div>JOB DESCRIPTION 
 
 
Build what's next in applied AI at JPMorganChase - where your work shapes how teams use intelligent systems at scale. You'll lead hands-on engineering for agentic and GenAI capabilities that power the LLM Suite platform. This role offers a mix of deep technical problem-solving, architecture ownership, and collaboration with talented builders. If you enjoy turning ambiguity into reliable production systems, you'll thrive here. Join a team that values craft, security, and learning. 
As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. You will own technical direction across architecture, implementation, and operational stability, with a strong focus on secure, high-quality software. You will partner with peers across engineering to identify patterns and improve standards, reliability, and scalability. You will help evolve the platform using modern public cloud services and agentic frameworks. You will contribute to a collaborative culture through communities of practice and emerging-technology events. You will explore and operationalize emerging patterns such as agent-to-agent communication, model context protocols, and agentic orchestration, turning early-stage concepts into scalable, production-ready capabilities. 
Job Responsibilities<ul><li>
Design, develop, and troubleshoot software solutions using creative approaches to solve complex technical challenges</li><li>
Write secure, high-quality production code and maintain algorithms that integrate with existing systems</li><li>
Create architecture and design artifacts for complex applications, ensuring design constraints are met through delivery</li><li>
Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks</li><li>
Implement GenAI services leveraging Azure OpenAI models and AWS Bedrock</li><li>
Identify hidden problems and patterns in data proactively to improve coding standards and system architecture</li><li>
Participate in software engineering communities of practice and events focused on emerging technologies</li></ul>
Required Qualifications, Capabilities, and Skills<ul><li>
Computer science degree or equivalent practical experience</li><li>
Hands-on experience with system design, application development, testing, and operational stability</li><li>
Proficiency in Python (FastAPI)</li><li>
Experience building microservices and APIs</li><li>
Experience with elastic compute, NoSQL databases, and messaging queues</li><li>
Strong understanding of the Software Development Life Cycle</li><li>
Solid grasp of CI/CD, application resiliency, and security</li></ul>
Preferred Qualifications, Capabilities, and Skills<ul><li>
Experience implementing GenAI services leveraging Azure OpenAI models and AWS Bedrock</li><li>
Proficiency working with large language models and building agents with LangGraph</li><li>
Experience developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages</li><li>
Experience with containerization</li><li>
Knowledge of agent-to-agent (A2A) communication concepts</li><li>
Familiarity with Model Context Protocol (MCP)</li>
Experience with agentic orchestrators, personal AI assistants, or AI skills development 
<li>
 
#LLMSuiteEngineering_jobs</li></ul>
ABOUT US
 
 
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. 
<div><div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. 
</div></div> 
 
ABOUT THE TEAM
 
 
Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.</div>

Applied AI ML Lead Software Engineer - LLM Suite Engineering

Hiscox

<div>
 
 Job Type
 
 
 
 Permanent
 
 
 
 Build a brilliant future with Hiscox
 
 
 
 
 Principal Machine Learning Engineer
 
 
 
 
 Location:
 
 London/York
 
 
 
 Why Hiscox London Market
 
 
 
 Hiscox London Market sits at the centre of global specialist insurance, tackling some of the most complex and unusual risks in the world. These are not commoditised problems, they demand deep expertise, strong judgement, and increasingly, sophisticated data and machine learning capabilities.
 
 
 We have a strong track record of putting AI into real production use, from augmenting underwriting decisions to shaping future market standards through partnerships and market‑first innovation. This is an environment where advanced ML systems are expected to operate reliably, safely, and at scale, not remain in experimentation.
 
 
 You&rsquo;ll join a culture that values technical excellence, ownership, and courage, where senior individual contributors are trusted to set direction, challenge thinking, and build platforms that matter. For a Principal Machine Learning Engineer, this is a chance to work on high‑impact ML systems, influence how AI is adopted across the London Market, and help shape the future of insurance.
 
 
 
 Role Purpose
 
 
 
 As a
 
 Principal Machine Learning Engineer (MLE)
 
 , you bring a wealth of experience in building, scaling, and operating production machine learning systems, and use that experience to provide deep technical leadership across machine learning engineering and MLOps.
 
 
 You play a key role in shaping the architectural strategy for production ML systems and the ML Platform, working closely with Data Science, Engineering, and Platform teams to define patterns, standards, and tooling that enable reliable, repeatable delivery at scale. Through hands‑on contribution, design leadership, and technical mentorship, you help teams navigate complex technical decisions and build robust, maintainable systems.
 
 
 A central focus of the role is enabling the organisation to move quickly without sacrificing quality, evolving the ML platform, supporting the transition from experimentation to production, and helping teams adopt modern engineering practices. This includes championing the effective and responsible use of AI‑assisted development tools as part of a broader approach to improving developer experience, system quality, and long‑term sustainability.
 
 
 Success in this role comes from the practical application of deep experience, strong architectural thinking, and the ability to help others build better systems that deliver real business value.
 
 
 
 Key Responsibilities
 
 
 
 
 Technical Leadership &amp; Ownership (Individual Contributor)
 
 
 
 <ul>
 <li>
 Act as the technical lead for Machine Learning Engineering and MLOps across London Market.
 </li>
 <li>
 Technically lead the most complex and business‑critical ML systems, from architectural design through to production operation.
 </li>
 <li>
 Define and evolve production ML patterns and best practices, covering deployment, orchestration, monitoring, retraining, and decommissioning.
 </li>
 <li>
 Lead deep technical decision‑making, balancing scalability, reliability, security, and developer experience.
 </li>
 <li>
 Contribute hands‑on to critical systems, frameworks, and platform components where the complexity or impact demands it.
 </li>
 <li>
 Define best practices and guardrails for the use of AI‑assisted coding tools, ensuring they are used to improve productivity and code quality without compromising maintainability or operational safety.
 </li>
 <li>
 Lead by example in applying AI‑assisted development techniques (e.g. for prototyping, refactoring, and accelerating complex engineering work) with strong engineering judgement.
 
 
 
 </li>
 </ul>
 
 ML Platform Strategy &amp; Build‑Out
 
 
 
 <ul>
 <li>
 Partner closely with Group and Platform teams to design, build, and evolve the ML Platform, ensuring it supports:
 </li>
 <ul>
 <li>
 Reusable and scalable deployment patterns
 </li>
 <li>
 CI/CD for machine learning
 </li>
 <li>
 Full model lifecycle management
 </li>
 <li>
 Monitoring, observability, and alerting
 </li>
 <li>
 Secure and compliant operation
 </li>
 </ul>
 <li>
 Shape platform standards and interfaces that enable consistent ML delivery across squads and value streams.
 </li>
 <li>
 Lead technical spikes and proof‑of‑concepts to evaluate new tools, approaches, and architectural patterns.
 </li>
 <li>
 Influence developer tooling choices so that AI‑assisted coding tools integrate safely with CI/CD, testing, and governance workflows.
 </li>
 <li>
 Ensure the platform enables fast, safe experimentation while supporting robust, long‑lived production systems.
 
 
 </li>
 </ul>
 
 Governance, Reliability &amp; Commercial Impact
 
 
 
 <ul>
 <li>
 Ensure ML systems meet architecture, security, compliance, and operational standards.
 </li>
 <li>
 Define and implement robust frameworks for monitoring technical health, model performance, and commercial impact of ML systems in production.
 </li>
 <li>
 Champion operational excellence across ML services, including monitoring, alerting, incident management, and post‑incident learning.
 </li>
 <li>
 Ensure clear ownership and lifecycle management for models and ML‑backed services.
 </li>
 <li>
 Promote responsible use of automation and AI‑assisted tooling in safety‑critical or regulated contexts.
 
 
 
 </li>
 </ul>
 
 Collaboration &amp; Influence
 
 
 
 <ul>
 <li>
 Work closely with the Data Science team to ensure a smooth and repeatable transition from experimentation to production.
 </li>
 <li>
 Collaborate with software engineers, product managers, and business stakeholders to deliver end‑to‑end ML‑driven solutions.
 </li>
 <li>
 Act as a senior technical voice in design reviews, architecture forums, and strategic discussions.
 </li>
 <li>
 Influence technical direction and standards through expertise, credibility, and collaboration rather than line management.
 
 
 
 </li>
 </ul>
 
 Technical Mentorship &amp; Capability Development
 
 
 
 <ul>
 <li>
 Provide hands‑on technical mentorship to Machine Learning Engineers and Data Scientists.
 </li>
 <li>
 Raise engineering standards by sharing best practices, patterns, and lessons learned from real production systems.
 </li>
 <li>
 Coach teams on the effective and critical use of AI‑assisted coding tools, reinforcing the importance of code review discipline, testing, and long‑term maintainability.
 </li>
 <li>
 Contribute to technical hiring, assessment, and onboarding from a senior engineering perspective.
 </li>
 <li>
 Help shape long‑term capability by identifying gaps in tooling, skills, and platform maturity.
 
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Bring
 
 
 
 
 Experience &amp; Background
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or a related quantitative field (or equivalent experience).
 </li>
 <li>
 Extensive experience as a senior or principal Machine Learning Engineer delivering production ML systems at scale.
 </li>
 <li>
 Proven track record of owning or shaping ML platforms, MLOps frameworks, or critical ML infrastructure.
 </li>
 <li>
 Experience operating in complex, cross‑functional environments (insurance or financial services experience is advantageous but not essential).
 
 
 
 </li>
 </ul>
 
 Technical Expertise
 
 
 
 <ul>
 <li>
 Exceptional Python skills in a machine learning engineering context, with strong software engineering fundamentals (OOP, testing, design patterns).
 </li>
 <li>
 Deep experience building, deploying, and operating production ML systems, including:
 </li>
 <ul>
 <li>
 Online and batch model serving
 </li>
 <li>
 Monitoring, alerting, and observability
 </li>
 <li>
 Retraining and lifecycle management
 </li>
 </ul>
 <li>
 Strong understanding of core data science concepts, sufficient to:
 </li>
 <ul>
 <li>
 Review and challenge modelling approaches
 </li>
 <li>
 Ensure models are production‑ready and correctly evaluated
 </li>
 </ul>
 <li>
 Hands‑on experience with a major cloud platform (AWS, GCP, or Azure), including containerised deployments.
 </li>
 <li>
 Expert knowledge of MLOps and CI/CD, including:
 </li>
 <ul>
 <li>
 Git‑based workflows
 </li>
 <li>
 Infrastructure as Code (e.g. Terraform)
 </li>
 <li>
 Automated testing and deployment pipelines
 </li>
 </ul>
 <li>
 Strong operational mindset, including APIs, logging, monitoring, reliability, and incident response.
 </li>
 <li>
 Working knowledge of SQL and integration of ML services into wider data and application ecosystems.
 </li>
 <li>
 Experience using AI‑assisted coding tools in a production engineering context, with a clear understanding of their benefits, limitations, and risks.
 
 
 </li>
 </ul>
 
 Why Join Us?
 
 
 
 This is an opportunity to shape the future of machine learning engineering at Hiscox, build a high-performing sub-chapter, and influence strategic decisions, while staying close to the craft you love. You&rsquo;ll have the autonomy to set standards, mentor talent, and explore emerging technologies, all within a collaborative and forward-thinking environment.
 
 
 
 Work with amazing people and be part of a unique culture
 
</div>

Principal Machine Learning Engineer

Alignerr

<div>
 
 About The Role
 
 
 
 What if your machine learning expertise could directly influence how the most advanced AI systems in the world think, reason, and write code? We're looking for experienced ML engineers in London to evaluate AI-generated machine learning solutions &mdash; catching errors, improving quality, and helping frontier AI models get genuinely better at one of the hardest things they do.
 
 
 This is a fully remote, flexible contract role. Work asynchronously on your own schedule, from wherever you are. No fixed hours, no meetings &mdash; just high-impact, expert work that matters.
 
 
 <ul>
 <li>
 Organization: Alignerr
 </li>
 <li>
 Type: Hourly Contract
 </li>
 <li>
 Location: Remote (UK-based)
 </li>
 <li>
 Commitment: Flexible, project-based
 
 
 </li>
 </ul>
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Review and evaluate AI-generated machine learning code &mdash; including Python, TensorFlow, PyTorch, and scikit-learn &mdash; for correctness, efficiency, scalability, and clarity
 </li>
 <li>
 Write high-quality ML solutions to modeling, data processing, and deployment problems across a range of difficulty levels
 </li>
 <li>
 Craft clear, developer-friendly explanations for model architecture decisions, code logic, and problem-solving approaches
 </li>
 <li>
 Identify edge cases, ambiguities, and weaknesses in problem statements, datasets, or AI-generated responses
 </li>
 <li>
 Help set the quality bar for how AI understands and produces machine learning code
 
 
 </li>
 </ul>
 
 Who You Are
 
 
 
 <ul>
 <li>
 Deeply fluent in machine learning &mdash; you know your way around model development, data preprocessing, training pipelines, and deployment
 </li>
 <li>
 Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
 </li>
 <li>
 Strong written communicator &mdash; able to explain complex ML concepts clearly and precisely
 </li>
 <li>
 Detail-oriented and rigorous &mdash; you catch what others miss and care about getting things right
 </li>
 <li>
 Self-motivated and comfortable working independently in an async environment
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 3&ndash;5+ years working on machine learning projects, pipelines, or MLOps
 </li>
 <li>
 Experience with model evaluation, cloud deployment, or production ML systems
 </li>
 <li>
 Bachelor's, Master's, or PhD in Computer Science, Machine Learning, or a related field
 </li>
 <li>
 Background in data labeling, RLHF, or other AI training workflows
 </li>
 <li>
 Prior experience with code review or technical writing
 
 
 </li>
 </ul>
 
 Why Join Us
 
 
 
 <ul>
 <li>
 Work on cutting-edge AI projects alongside leading research labs and top AI teams
 </li>
 <li>
 Fully remote and async &mdash; work when and where it suits you, with no minimum hour commitments beyond project needs
 </li>
 <li>
 Freelance autonomy with the structure of meaningful, task-based work
 </li>
 <li>
 Your contributions directly improve AI models used by top research labs and enterprise teams worldwide
 </li>
 <li>
 High-performing contributors take on expanded responsibilities and lead new programs
 </li>
 <li>
 Potential for ongoing work and contract extension as new projects launch
 </li>
 </ul>
</div>

Software Engineer – Machine Learning (AI Training)

Explore 531+ Machine learning lead in London this July. Find roles across top companies and apply now to boost your career.

531 machine learning lead jobs In London

Software Engineer (Leadership) - Machine Learning

Software Engineer (Leadership) - Machine Learning

Lead Data Scientist

VP, Head of Data Science

Applied AI ML Lead Software Engineer - LLM Suite Engineering

Principal Machine Learning Engineer

Software Engineer – Machine Learning (AI Training)