mlops engineer

Ciklum

<p></p><div><div><div><div><div><div><div><div><div><div><div><b>Ciklum</b> is looking for a <b>Expert Agentic AI Engineer</b> to join our team full-time in the UK .<br>
We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live.</div><p><b>
About the role:</b></p><p>
As a Expert Agentic AI Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.</p><p><b>
Responsibilities:</b></p><ul><li>
Design, build, train, and deploy production-grade Machine Learning, Deep Learning, or Natural Language Processing (NLP) models</li><li>
Optimize ML models for enterprise-scale latency, throughput, and performance, ensuring flawless integration with data warehouses and automated workflow bots</li><li>
Partner with Data Engineers to engineer high-quality data pipelines, automated feature stores, and secure data preprocessing routines</li><li>
Establish and scale MLOps workflows to handle model lineage tracking, code versioning, automated validation gates, and continuous deployment pipelines</li><li>
Set the core technical direction for AI engineering across squads, evaluate emerging AI methodologies, and provide high-level mentorship to senior team members</li></ul><p><b>
Requirements:</b></p><ul><li>
5+ years (Senior) or 8+ years (Expert) of professional experience developing, shipping, and maintaining machine learning models in live production environments</li><li>
Agentic Frameworks: Hands-on experience building autonomous workflows, custom plugins, and orchestration logic using Microsoft Copilot Studio or semantic kernels</li><li>
Cloud AI Infrastructure: Proven experience deploying and fine-tuning generative AI models, prompt flow, and vector databases within Azure AI Foundry (formerly Azure AI Studio)</li><li>
Tool Integration: Strong background in connecting LLMs to external APIs, enterprise data sources, and robotic process automation (RPA) tools to enable autonomous action execution</li><li>
Elite proficiency in Python paired with extensive experience using core ML libraries and frameworks (such as PyTorch, TensorFlow, Scikit-Learn, or Hugging Face)</li><li>
Hands-on experience working with MLOps tracking tools and cloud-based AI infrastructure ecosystems (such as MLflow, Kubeflow, AWS SageMaker, or Azure ML)</li><li>
Strong computer science fundamentals, including advanced knowledge of data structures, algorithmic complexity, and clean code principles. a formal degree in Computer Science, Data Science, Mathematics, or a highly quantitative field is strongly preferred</li></ul><p><b>
What`s in it for you?</b></p><ul><li>
Strong community: Work alongside top professionals in a friendly, open-door environment</li><li>
Growth focus: Take on large-scale projects with a global impact and expand your expertise</li><li>
Tailored learning: Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications</li><li>
Endless opportunities: Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge technologies</li><li>
Care: Healthcare, Basic Life Insurance, Short and Long-term disability insurance according to the Company&rsquo;s Benefit Plans</li></ul><p><b>
About us:</b></p><p>
At Ciklum, we are always exploring innovations, empowering each other to achieve more, and engineering solutions that matter. With us, you&rsquo;ll work with cutting-edge technologies, contribute to impactful projects, and be part of a One Team culture that values collaboration and progress. In the UK, Ciklum is growing fast&mdash;inviting experienced professionals to lead digital transformation alongside Fortune 500 clients. Be part of a company where innovation and impact go hand in hand.</p><p><b>
Explore, empower, engineer with Ciklum!</b></p><p>
Interested already? We would love to get to know you! Submit your application. We can&rsquo;t wait to see you at Ciklum.</p><p>
#LI-VH1</p></div>
</div></div></div></div></div></div><div></div><div><div><div><div><div><div><p>REQUIRED SKILLS</p>
<div><ul><p>Agentic AI</p>
</ul></div></div></div></div></div></div></div><div></div><div><div><div><div><div><div><div>
</div></div></div></div></div></div></div><div><div><div><div><div><div><p>JOB INFO</p>
<div><div><div><ul><div><div>Job Identification</div>
<div>3619</div>
</div><div><div>Job Category</div>
<div>Intelligent Automation</div>
</div><div><div>Posting Date</div>
<div>07/03/2026, 02:34 AM</div>
</div><div><div>Locations</div>
<div> <div></div><div><div>London
</div></div>(Hybrid)</div></div></ul></div></div></div></div></div></div></div></div></div></div></div></div><p></p>

Expert Agentic AI Engineer

Accenture

<div><p><b>YOU ARE</b></p><p>
As a hands-on Infrastructure architect, you are an early-career engineer who learns and grows while contributing hands-on to the AI and machine learning infrastructure that powers real-world applications. Under the guidance of senior architects and engineers, you'll develop practical skills in coding, testing, configuring, deploying, monitoring, and troubleshooting AI systems and the infrastructure they run on. Day to day, you'll write and test code and deployment scripts, help configure cloud and on-premises compute resources such as GPU clusters and distributed training environments, deploy AI systems and models into production, and support data pipelines that feed AI and ML workflows. You'll learn to monitor AI systems and infrastructure health across both InfraOps and MLOps disciplines, perform AI monitoring to track model and system performance, and troubleshoot issues across the computational stack with mentorship and support. This is a hands-on, learning-focused where you build expertise across modern tools and platforms &mdash; including container orchestration, model serving, CI/CD pipelines, InfraOps, MLOps, and AI monitoring &mdash; while making meaningful contributions to infrastructure that enables AI-driven busin</p><p>
ess outcomes.</p><p></p><p><b>
THE WORK</b></p><ul><li>
Write, test, and debug code and scripts for AI infrastructure tasks, including automation and tooling, under the guidance of senior engineers.</li><li>
Develop and maintain infrastructure and software deployment scripts to support reliable, repeatable releases of AI systems and models.</li><li>
Configure and provision compute resources across cloud and on-premises environments, including GPU clusters and distributed training setups.</li><li>
Deploy AI systems and machine learning models into production infrastructure, following established processes and best practices.</li><li>
Deploy data pipelines that feed AI and ML workflows, ensuring data is available, clean, and reliable.</li><li>
Assist with container orchestration and model serving, learning tools such as Docker, Kubernetes, and model deployment frameworks.</li><li>
Support and maintain CI/CD pipelines for automating the build, test, and deployment of AI infrastructure and applications.</li><li>
Monitor AI systems and infrastructure health across InfraOps and MLOps disciplines, tracking performance, reliability, and resource utilization.</li><li>
Perform AI monitoring to track model performance, detect drift or degradation, and surface issues for review.</li><li>
Troubleshoot and help resolve issues across the computational stack &mdash; hardware, networking, software, and models &mdash; with mentorship and support.</li><li>
Document configurations, processes, and procedures to maintain clear, repeatable, and shareable knowledge across the team.</li><li>
Collaborate with senior architects and engineers, participating in code reviews, team discussions, and knowledge-sharing sessions to grow technical skills.</li><li>
Apply security, cost-efficiency, and scalability best practices as you learn them, contributing to well-managed and responsible infrastructure.</li></ul></div>
<br>
<div><p><b>EDUCATION</b></p><ul><li>
Bachelor's Degree in Computer Science, Computer Engineering, related Engineering field</li></ul><p></p><p><b>
BASIC (REQUIRED) QUALIFICATION</b></p><ul><li>
Work or coursework experience with AI/ML or Computer engineering or Computer science.</li><li>
Coding, building, monitoring, troubleshooting applications of AI/ML models; selecting, designing and infrastructure for deploying and running them on premise or on public cloud.</li><li>
Strong understanding of AI and machine learning as a subject.</li><li>
Strong understanding of computing infrastructure a subject, preferred knowledge of AI infrastructure.</li><li>
Proficiency in programming languages such as Python, Java, or C++.</li></ul></div><p></p>

AI Infrastructure Architecture Analyst

Bloomberg

<div>
 Location
 <br/>
 <br/>
 London
 <br/>
 <br/>
 Business Area
 <br/>
 <br/>
 Engineering and CTO
 <br/>
 <br/>
 Ref #
 <br/>
 <br/>
 10049302
 <br/>
 <br/>
 <strong>
  Description &amp; Requirements
  <br/>
  <br/>
 </strong>
 Bloomberg&rsquo;s Engineering AI department has 400+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products. At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.
 <br/>
 <br/>
 Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions.
 <br/>
 <br/>
 Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.
 <br/>
 <br/>
 We are looking for Senior ML Platform Engineers with strong expertise and passion for building platforms for (Gen) AI applications.
 <br/>
 <br/>
 As a Senior ML Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed AI development life cycle to enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as, Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source.
 <br/>
 <br/>
 <strong>
  Join the AI Group as a Senior ML Platform Engineer and you will have the opportunity to:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Architect, build, and diagnose multi-tenant AI platform systems
  </li>
  <li>
   Work closely with AI application teams to design seamless workflows for continuous model training, inference, and monitoring
  </li>
  <li>
   Work with AI experts to understand workflows, pinpoint, and resolve inefficiencies, and to inform the next set of features for the platforms
  </li>
  <li>
   Collaborate with open-source communities and AI application teams to build a cohesive MLOps experience
  </li>
  <li>
   Design CI/CD automation frameworks that incorporate regulatory requirements
  </li>
  <li>
   Develop cloud-native deployment patterns for AI systems across environments
  </li>
  <li>
   Troubleshoot and debug user issues
  </li>
  <li>
   Provide operational and user-facing documentation
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  We are looking for a Senior ML Platform Engineer with:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Proven years of experience working with an object-oriented programming language (Python, Go, etc.)
  </li>
  <li>
   Experience designing cloud-native, distributed platforms
  </li>
  <li>
   Strong knowledge of Kubernetes, Argo, and container orchestration technologies
  </li>
  <li>
   Previous experience with modern CI/CD tools and GitOps workflows
  </li>
  <li>
   Familiarity with implementing automation for model development lifecycles
  </li>
  <li>
   A proactive mentality and ability to collaborate with peers, stakeholders, and management
  </li>
  <li>
   A Degree in Computer Science, Engineering, Mathematics, or similar field of study or equivalent work experience
  </li>
  <li>
   An understanding of Computer Science fundamentals such as data structures and algorithms
   <br/>
   <br/>
  </li>
 </ul>
 We give back to the technology community and you can read more about our outreach at:
 <br/>
 <br/>
 If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
 <br/>
 <br/>
 Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.
</div>


Senior ML Platform Engineer - Artificial Intelligence

Talan

<div><b>Company Description</b><p><br>
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI).</p><b><br>
Job Description</b><p><br>
As our AI practice scales, we are seeking an experienced AI Architect / Engineer to act as the senior technical authority shaping how we design and deliver next-generation AI solutions. This is a role for someone who has moved beyond building individual models to architecting entire systems: agentic platforms, LLM-powered applications, and the production infrastructure that makes them dependable at enterprise scale.</p><p>
You will sit at the intersection of strategy and delivery, operating across multiple client engagements simultaneously. In the early phases you will shape solutions, validate technical approaches, and translate ambiguous business problems into robust, deployable architectures. As engagements mature, you will provide the technical oversight that keeps delivery teams aligned to the original design intent. Your influence will be felt in pre-sales conversations, solution blueprints, and the technical standards that define how our practice builds.</p><p>
This is a hands on architectural role, not a purely advisory one. We expect you to remain close to the code, to prototype where it accelerates a decision, and to set a credible technical example for the engineers and data scientists you guide.</p><p><b>
Required skills &amp; experience:</b></p><ul><li>
Lead end-to-end solution architecture for AI and LLM-based systems, spanning data, integration, infrastructure, and deployment.</li><li>
Design agentic architectures and multi-agent orchestration patterns, defining how LLMs, tools, APIs, and retrieval layers interact reliably.</li><li>
Shape early-stage engagements (scoping, solutioning, estimation, and pre-sales) turning client ambition into deliverable technical plans.</li><li>
Provide technical validation and quality oversight across several concurrent projects, mitigating risk before it reaches delivery.</li><li>
Define LLM integration and prompting strategies, including RAG, fine-tuning, evaluation, and guardrailing approaches.</li><li>
Establish MLOps and LLMOps practices that ensure solutions are observable, testable, and production ready.</li><li>
Set architectural standards, reusable patterns, and reference implementations that raise the quality bar across the practice.</li><li>
Partner with Responsible AI colleagues to embed safety, security, and governance into solution designs from the outset.</li></ul><br>
<b>
Qualifications</b><p><b><br>
To qualify for this role, you must have:
</b></p><ul><li>Minimum 5 years in AI architecture or AI engineering, ideally 10+, with a track record of production deployments.</li><li>
Deep expertise in LLMs, agent frameworks (e.g. LangGraph, AutoGen, Semantic Kernel), API design, and orchestration.</li><li>
Strong cloud engineering experience.</li><li>
Proven MLOps / LLMOps capability &mdash; CI/CD for models, monitoring, evaluation, and cost optimisation.</li><li>
Hands-on software engineering background (Python and modern tooling) underpinning your architectural decisions.</li><li>
Comfort managing multiple engagements at once, with pragmatic judgement on trade-offs and delivery risk.</li></ul><p><b>
Ideally, you&rsquo;ll also have, but not essential:</b></p><ul><li>
Experience in consulting, professional services, or pre-sales environments.</li><li>
Exposure to enterprise-scale, regulated AI deployments (financial services, public sector, healthcare).</li><li>
Familiarity with vector databases, knowledge graphs, and advanced retrieval techniques.</li><li>
Relevant cloud or AI certifications.</li></ul><p><b>
You must be:</b></p><ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul><p></p><p><br>
#TalanUK #LI-HB1</p><b><br>
Additional Information</b><p><b><br>
Compensation &amp; Benefits Package:</b></p><ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul><p><b>
Why join:</b></p><p>
You will be a founding technical voice in a practice that is investing decisively in AI. The work is varied, intellectually demanding, and commercially significant, you will shape solutions that reach production, not slideware. You will have the autonomy to define how we build, the support of a collaborative multidisciplinary team, and a clear platform to grow into a practice-leading technical figure.</p></div>

AI Architect / Engineer (Agentic AI & LLM Architecture)

HOMETRACK

<div><p>Hometrack is redefining the mortgage journey for lenders, brokers, and consumers by delivering market-leading valuation and property data services to the financial, property, and technology industries. Our key commercial and go-to-market segment is in financial services, primarily mortgage lenders, including nine of the top 10 mortgage providers.</p><p>
At Hometrack, we are looking for an experienced Senior Machine Learning Engineer, to translate POC model code from data science and analytics into robust pipelines and live APIs.</p><p></p><p>
Responsibilities:</p><ul><li>
Oversee the deployment of machine learning models into production, ensuring they perform well in real-world conditions and monitoring their performance over time.</li><li>
Work closely with data scientists, software engineers, product managers, and stakeholders to integrate machine learning solutions into our products and services.</li><li>
Develop automated workflows for model retraining, testing, and deployment to streamline the machine learning lifecycle.</li><li>
Advocate for and implement best practices in software engineering, including code reviews, continuous integration, and continuous delivery (CI/CD) for machine learning models.</li></ul><p></p><p>
Requirements:</p><ul><li>
Strong understanding of machine learning applications, development life cycle processes and tools: CI/CD, version control, testing frameworks, MLOps.</li><li>
Strong Python experience and knowledge, with the ability to write stable, scalable and maintainable code.</li><li>
Experience with data science Python libraries such as Sckit-learn, Pandas, NumPy, PyTorch, PySpark, LightGBM.</li><li>
Have worked with a cloud service, such as AWS.</li><li>
Familiarity developing Infrastructure as code (e.g Terraform, cloudformation).</li><li>
Have some experience with data engineering, building data pipelines with PySpark, SQL (E.g in Databricks, Glue) to power machine learning applications.</li><li>
Comfortable working with Docker and containerised applications.</li><li>
Experience leveraging AI native engineering tooling.</li><li>
Passion for building products that meet customer needs and business objectives.</li><li>
Strong sense of responsibility and a track record of delivering high-quality results in a fast-paced environment.</li></ul><br>
<b>
Benefits</b><br>
<ul><li>
Everyday Flex - greater flexibility over where and when you work</li><li>
25 days annual leave + extra days for years of service</li><li>
Day off for your birthday, house move, good deed day, and digital detox day</li><li>
Cycle to work and electric car schemes
</li><li>Free Calm App membership
</li><li>Enhanced Paternity Leave
</li><li>Fertility Treatment Financial Support
</li><li>Group Income Protection and private medical insurance</li><li>
Gym on-site in London &ndash; or membership in regional offices</li><li>
7.5% pension contribution by the company</li><li>
Discretionary annual bonus up to 10% of base salary</li><li>
Talent referral bonus up to &pound;5K</li></ul></div>

Senior Machine Learning Engineer

Worldpay

<div><p><b>Ready to take your career global?</b></p><p>
Make your mark at one of the biggest names in payments.</p><p>
We are seeking an experienced <b>Senior ML Software Engineer</b> to join our Data Science Enablement team. You will be the primary software engineering expert for a product area, working as part of a cross-functional agile team and owning the successful launches and ongoing operations of high-profile products in production. Your focus will be on driving new feature delivery, maintaining operational excellence, and collaborating on enhancements to our shared ML platform. You will work closely with cross-functional collaborators&mdash;including ML research engineers, product managers, and platform engineers&mdash;to deliver scalable, reliable, and low-latency ML solutions.</p><p>
In addition to technical expertise, this job requires strong collaboration skills.</p><p></p><p><b>
What you&rsquo;ll own</b></p><p>
Feature Development &amp; Delivery:</p><ul><li>
Design, implement, and deploy new features and enhancements to ML products, collaborating with Product and ML Research teams to refine requirements.</li></ul><p>
Technical Ownership and Stewardship:</p><ul><li>
Technical ownership of existing and new production ML products in your area, ensuring alignment of technical investments with business goals (in collaboration with a product owner) and engineering best practices.</li><li>
End-to-end technical stewardship of ML products, ensuring ongoing reliability and performance.</li></ul><p>
Contribute to ML platform:</p><ul><li>
Contribute to the evolution of the shared ML platform alongside other engineers to drive best practices and shared tooling across all products.</li></ul><p>
Operational Excellence:</p><ul><li>
Maintain and improve automated CI/CD pipelines, testing frameworks, and monitoring/logging, ensuring high operational standards.</li><li>
Conduct comprehensive code reviews to enforce coding standards, improve code quality, and share knowledge.</li></ul><p>
Continuous Improvement:</p><ul><li>
Identify and implement opportunities for process, tooling, and system improvements, proactively addressing technical debt and scaling challenges.</li></ul><p>
Release Management:</p><ul><li>
Oversee pre-release testing, coordinate releases and ensure smooth enablement of new features.</li></ul><p>
Leadership:</p><ul><li>
Provide technical guidance and support to other engineers and data scientists to solve complex technical challenges.</li><li>
Mentor and coach other engineers, supporting their professional growth.</li><li>
Foster a culture of collaboration, continuous improvement, and knowledge sharing.</li></ul><p>
Act Like an Owner:</p><ul><li>
Proactively identify and resolve blockers, navigate processes, and independently seek out information and connect with relevant teams to drive solutions in the face of ambiguity.</li><li>
Operate with a strong sense of urgency, consistently prioritizing and executing tasks to meet timelines and deliver results.</li></ul><p></p><p><b>
What you&rsquo;ll bring</b></p><ul><li>
5+ years as an ML-focused software engineer, ML Engineer, MLOps Engineer, or similar, with hands-on production experience</li><li>
Proven expertise with ML model deployment, API design, and integration into production environments</li><li>
Strong Python programming and relevant ML/data libraries</li><li>
Experience with containerization, orchestration, and AWS cloud services</li><li>
Building and operating CI/CD pipelines</li><li>
Monitoring, troubleshooting, and optimizing production ML systems</li><li>
Pre-release testing and release management</li><li>
Demonstrated ability to work independently, navigate ambiguity, and deliver results</li><li>
Excellent communication skills and ability to collaborate both within engineering organizations and on cross-functional teams</li><li>
Experience with OpenAPI, FastAPI, or similar</li></ul><p></p><p><b>
It&rsquo;s a bonus if you have</b></p><ul><li>
Experience with MLFlow, model versioning, and storage</li><li>
Familiarity with Databricks or similar platforms</li><li>
Experience supporting high-volume, real-time data products</li><li>
Automated testing and validation frameworks</li><li>
Experience designing and configuring low-latency databases to serve real-time features, such as DynamoDB</li><li>
Experience with Terraform Cloud</li><li>
Experience in large companies, mature engineering teams, and/or highly regulated industries</li><li>
AI-assisted coding experience (e.g. GitHub Copilot)</li></ul><p></p><p><b>
Why Join Us?</b></p><ul><li>
Impact: Play a key role as the technical owner of high-profile ML products delivering meaningful business impact to merchants and advancing key pillars of the company&rsquo;s strategy. Your work will directly influence the reliability, scalability, and evolution of critical production systems.</li><li>
Autonomy: Take end-to-end technical ownership of your product area, with the freedom and responsibility to drive technical solutions, shape best practices, and deliver results in a fast-paced, supportive environment.</li><li>
Collaboration: Join a cross-functional, high-performing team where your expertise is valued and your contributions make a real difference.</li></ul><p></p><p><b>
About the team</b></p><p>
Our inclusive and global teams win together every day. We&rsquo;re proud to have the best minds in the industry, whom you can learn from as you grow your career. The people, the energy, and the connections are unmatched. Come and be part of an ever-evolving company and get dynamic opportunities that transcend borders.</p><p></p><p><b>
What makes a Globalpayer?</b></p><p>
Globalpayers think like a client, act like an owner, and win as one team. We&rsquo;re curious and innovative &ndash; always finding better ways to deliver impact. We empower each other to make decisions, and our passion drives excellence in everything we set out to do.</p><p></p><p>
Does this sound like you? Then you sound like a Globalpayer. Apply now to take your career global.</p><p></p><p>
#LI-AB1</p></div>

Senior ML Software Engineer

Alignerr

<div>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 <ul>
  <li>
   Organization: Alignerr
  </li>
  <li>
   Type: Hourly Contract
  </li>
  <li>
   Location: Remote (UK-based)
  </li>
  <li>
   Commitment: Flexible, project-based
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What You'll Do
  <br/>
  <br/>
 </strong>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Who You Are
  <br/>
  <br/>
 </strong>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice to Have
  <br/>
  <br/>
 </strong>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Why Join Us
  <br/>
  <br/>
 </strong>
 <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)

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