software engineer

machine learning engineer

ai engineer

senior software engineer

full stack engineer

robotics engineer

HCLTech

City Of London, England
<br>Job Summary
<br><br>
<b>Job Title:</b> Physical AI Engineer (Robotics & Agentic Systems)
<br>We are looking for an engineer to build the Physical AI solutions using Robotics and edge devices on Google stack. You will integrate Deepmind Robotics model with Gemini 3 foundation models to create autonomous agents that perceive, reason, and act in dynamic industrial environments. Your work will involve moving Physical AI from simulation (MuJoCo-Warp) to production-grade hardware at scale.
<br><br>
Key Responsibilities
<br><br>
Key Responsibilities
<br><ul>
<li>Model Integration: Deploy Gemini Robotics-ER (Embodied Reasoning) models to enable robots to understand natural language instructions and physical causality.</li>
<li>Workflow Orchestration: Utilize the Gemini Enterprise Agent Platform to build agentic workflows that connect cloud-based reasoning with edge-based execution.</li>
<li>Simulation & Training: Use MuJoCo-Warp and G4 VMs (NVIDIA Blackwell) to run high-fidelity simulations, generating synthetic data to train robots on complex edge cases.</li>
<li>Hardware Abstraction: Work within Intrinsic Flowstate to develop hardware-agnostic "Skills" (robotic behaviors) that can be deployed across various robotic arms and sensors (Universal Robots, Foxconn, etc.).</li>
<li>System Optimization: Implement the JAX AI Stack (JAX, Flax, Optax) for efficient, accelerator-oriented computation on Google TPUs and NVIDIA GPUs.</li>
</ul>
Skill Requirements
<br><br>
Technical Requirements
<br>Category Stack Components
<br>Foundation Models Gemini 1.5/3.0, RT-2 (Robotics Transformer), Gemini Robotics-ER
<br>Software Platform Intrinsic Flowstate, ROS 2 (Robot Operating System), Python
<br>Compute & Infra Google Cloud Vertex AI, Google Distributed Cloud (Edge), TPUs
<br>Physics Engines MuJoCo-Warp, NVIDIA Isaac Sim integration
<br>Data & ML JAX, XLA (Accelerated Linear Algebra), Orbax (Checkpointing)
<br><br>
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Principal Engineer

Humanoid

<div>
 <p>
  Here at Humanoid, we believe in a future where robots amplify human potential. That&rsquo;s why we&rsquo;ve set out on a mission to build the world&rsquo;s most capable, commercially-scalable, and safe humanoid robots. We&rsquo;re bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we&rsquo;re growing the team to take it even further.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   About The Role
  </strong>
 </p>
 <p>
  We're hiring a
  <strong>
   VLA Pre-training Engineer (Deep Learning)
  </strong>
  to join our Autonomy team based in London.
 </p>
 <p>
  In this role you will you will work on all aspects of training capable policies, be it pre-training of a base model on a diverse multi-embodiment corpus of trajectories, fine-tuning a policy to perform a specific task well, curating data collection processes or exploring productive ways to generate and use synthetic data. This is primarily a deep learning-focused role, so we are looking for experience solving real problems using modern neural networks, while experience in robotics isn&rsquo;t strictly required. However if you don&rsquo;t have such experience, be prepared that you&rsquo;d need to familiarize yourself with a new domain quickly.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What You'll Do
  </strong>
 </p>
 <ul>
  <li>
   Post-train policies via behaviour cloning and RL; own the full loop from data to deployment.
  </li>
  <li>
   Partner with the Data Collection team to drive collecting new data: specify what good data looks like, identify failure modes, ensure diversity and coverage.
  </li>
  <li>
   Work closely with external partners to ensure steady supply of high-quality pretraining-scale data.
  </li>
  <li>
   Run pre-/mid-/post-training on VLA stack; explore new modalities and architecture changes.
  </li>
  <li>
   Build and maintain continuous pipelines: ingest synthetic data and teleop logs, version them, apply weak‑supervision labelling, curate balanced datasets, and auto‑surface fresh failure cases into retraining.
  </li>
  <li>
   Work with MLOps &amp; Data Platform teams to scale distributed training and optimize models for real‑time edge inference.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What We're Looking For
  </strong>
 </p>
 <ul>
  <li>
   3+ years building deep‑learning systems (industry or research) with shipped models or published artifacts to show for it.
  </li>
  <li>
   Deep hands‑on experience with at least one of: LLMs, VLMs, or image/video generative models &mdash; architecture, training, and inference.
  </li>
  <li>
   Experience with deep learning infrastructure: streaming datasets, checkpointing &amp; state management, distributed training strategies.
  </li>
  <li>
   Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code.
  </li>
  <li>
   Familiarity with modern software engineering practices.
  </li>
  <li>
   You document experiments clearly and communicate trade‑offs crisply.
  </li>
 </ul>
 <p>
  <em>
   Nice to have
  </em>
 </p>
 <ul>
  <li>
   Robotics or autonomous driving experience.
  </li>
  <li>
   Experience applying RL to LLMs or robotics.
  </li>
  <li>
   Experience with VLA (vision-language-action) models.
  </li>
  <li>
   Proven productization of deep nets (latency/throughput constraints, telemetry, on‑device optimization).
  </li>
  <li>
   Publications at top-tier deep learning conferences or equivalent open‑source contributions.
  </li>
  <li>
   Familiarity with OpenVLA, Physical Intelligence (&pi;) models, or similar open source VLA frameworks.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What We Offer
  </strong>
 </p>
 <ul>
  <li>
   ompetitive equity: stock options with meaningful upside as we scale.
  </li>
  <li>
   30+ days time off, including 23 days annual leave, all UK bank holidays, and additional company closure days (including Christmas&ndash;New Year shutdown).
  </li>
  <li>
   Private healthcare, including virtual and in-person care.
  </li>
  <li>
   Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.
  </li>
  <li>
   Free daily breakfast, catered lunch, and snacks in-office.
  </li>
  <li>
   Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.
  </li>
  <li>
   Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.
  </li>
 </ul>
</div>


VLA Pre-training Engineer (Deep Learning)

McKinsey & Company

<div><div><div><div><div><div><div>Job ID: 109890</div></div></div></div><div></div><div><ul><div>
London</div><div>
Madrid</div></ul></div><div></div><div><div><div><br>
</div></div></div></div><div><p>
Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You&rsquo;ve come to the right place.</p><div><p>
YOUR IMPACT</p><div><div>
You will be part of QuantumBlack Labs and the Robotics and Physical AI team within our Advanced Industries Sector, a group of engineers, scientists, product managers, and machine learning specialists building a first of its kind physics AI capability that accelerates and scales how the world designs and builds physical systems.</div><div></div><div>
Our team is responsible for:</div><div><ul><li>
Building multi-physics simulation frameworks, digital twins, and surrogate models that stand in for slow, expensive physics solvers</li><li>
Applying physics-informed machine learning and robotics to real-world engineering systems across advanced industries, from chip design to aircraft manufacturing</li><li>
Deploying scalable, production grade tools on HPC infrastructure that embed our distinctive technical approach and engineering knowledge for industrial clients</li></ul></div><div>
You will lead technical workstreams on client engagements, building multi-physics simulation frameworks and digital twins, developing surrogate and machine learning models, applying physics-informed machine learning to real-world engineering systems, deploying scalable production tools on HPC infrastructure, and translating computational insights into strategic recommendations and solutions that deliver measurable impact for clients.</div><div></div><div>
You&rsquo;ll create surrogate models that replace costly simulations, compress design cycles from weeks to minutes, and bring autonomy to robotic systems on the factory floor. Collaborating with global, multidisciplinary teams, you&rsquo;ll drive innovation, develop impactful technologies, and grow as a leader in physical AI.</div><div></div><div>
You will work with diverse and complex engineering data sets, develop scientific software products, and write optimized code to enhance our internal tools. Collaborating with scientists, engineers, and designers, you will leverage advanced math, statistics, and machine learning to deliver impactful solutions and grow the firm&rsquo;s capacity to deliver at scale.</div><div></div><div>
Your work will help clients address their most pressing challenges by deploying cutting-edge technology and amplifying impact across industries. You will also contribute to the broader physical AI community by writing papers, presenting at conferences, and sharing knowledge with colleagues.</div><div></div><div>
You will be based in London or Madrid and collaborate closely with scientists, data engineers, machine learning engineers, designers, and product managers around the world. Together, you&rsquo;ll work on interdisciplinary projects to solve complex engineering challenges across a range of industries, leading the development and application of cutting-edge physics AI solutions that drive measurable business impact.</div><div></div><div>
You&rsquo;ll grow as a technologist and leader in a collaborative, multidisciplinary environment, pushing the boundaries of innovation while shaping the future of physical AI and robotics.</div></div></div><div></div><div><p>
YOUR GROWTH</p><div><p>
Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.</p><p></p><p>
In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues&mdash;at all levels&mdash;will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won&rsquo;t find anywhere else.</p><p></p><p>
When you join us, you will have:</p><p></p><div><ul><li>
Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.</li><li>
A voice that matters: From day one, we value your ideas and contributions. You&rsquo;ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.</li><li>
Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm&rsquo;s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you&rsquo;ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.</li><li>
World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.</li></ul></div></div></div></div></div><div><div><div><p>
YOUR QUALIFICATIONS AND SKILLS</p><div><div><ul><p>
Advanced graduate degree (M.S. or Ph.D.) in computational mechanics, materials science, mechanical/aerospace/nuclear engineering, computational physics, or a closely related engineering or physical science field required; significant industry or national laboratory experience in applied simulation or scientific machine learning may apply.</p><p>
Demonstrated ability to develop high-quality engineering or scientific code (e.g., in Python, C++).</p><p>
Demonstrated fluency with statistical sampling, machine learning, and data science techniques.</p><p>
Simulation experience, PyTorch, ML/AI/Data Science a plus.</p><p>
Excellent organizational capabilities, including the ability to initiate tasks independently and see them through to completion.</p><p>
Proficient in rational decision-making based on data, facts, and logical reasoning.</p><p>
Ability to create work-product-focused materials / outputs, which may include PowerPoint decks, Excel models, articles, or other written deliverables.</p><p>
Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment.</p><p>
Ability to work or attend meetings outside of traditional business hours or take on projects with limited or no notice at times.</p><p>
Ability to travel to and work in varying environments that may be challenging and/or not accessible (e.g., manufacturing facilities, etc.).</p><p>
Strong communication skills, both verbal and written, in English and local office language(s), with the ability to adjust your style to suit different perspectives and seniority levels.</p></ul></div></div></div></div></div><div><div><div><div>
Please review the additional requirements regarding essential job functions of McKinsey colleagues.</div>
<div>Our unwavering commitment to integrity drives everything we do, guiding us to always act in the best interests of our clients, our people, and the communities we serve.</div></div></div></div></div>

Physical AI Data Scientist - QuantumBlack Labs

<div><p>Here at Humanoid, we believe in a future where robots amplify human potential. That&rsquo;s why we&rsquo;ve set out on a mission to build the world&rsquo;s most capable, commercially-scalable, and safe humanoid robots. We&rsquo;re bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we&rsquo;re growing the team to take it even further.</p><p></p><h2 class="jobSectionHeader"><b>
About the role:
</b></h2><p>We are looking for a Software Engineer to work on the systems that let operators author, deploy, and manage robot workflows at scale. This sits at the intersection of backend infrastructure and product - you'll build the services that coordinate fleets of robots, the tooling that lets operators express what they want robots to do, and the interfaces that give visibility into what's actually happening on the floor.</p><p>
This is a full-stack role with a strong backend lean. You'll work closely with the robotics, AI, and product teams to build systems that are real-time, multi-tenant, and mission-critical.</p><p></p><h2 class="jobSectionHeader"><b>
What You&rsquo;ll Do</b></h2><ul><li><p>
Build and maintain backend services that coordinate robot fleets at runtime: workflow state management, event logging, and the APIs that robots, operators, and third-party systems use to interact with the platform</p></li><li><p>
Develop and evolve the workflow authoring experience - tooling that lets operators define, deploy, and incrementally refine robot workflows in natural language, without needing to understand the underlying representation</p></li><li><p>
Build on-robot services that enable remote control, workflow execution, state reporting, and diagnostics</p></li><li><p>
Own the data infrastructure that tracks workflow execution: event logs, conformance metrics, and the audit trails that let operators understand what robots are doing and why</p></li><li><p>
Build and maintain reliable, secure cloud infrastructure for running these services, including deployment pipelines, observability, and alerting</p></li><li><p>
Implement testing and validation pipelines to catch regressions across the UI, backend, and on-robot services - including simulation-based workflow validation before changes hit production</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
What We&rsquo;re Looking For</b></h2><ul><li><p>
Strong backend engineering skills in Python, Go, or similar</p></li><li><p>
Solid understanding of API design, data modelling, and the tradeoffs in distributed systems (consistency, concurrency, fault tolerance)</p></li><li><p>
Experience with cloud infrastructure and deployment: containerisation, CI/CD, infrastructure-as-code</p></li><li><p>
Comfort working across the stack from frontend to backend</p></li><li><p>
Experience with observability and alerting in systems where failures have real operational consequences</p></li><li><p>
Good instincts for where complexity should live and how to keep systems debuggable and understandable as they grow</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Nice To Have</b></h2><ul><li><p>
Familiarity with workflow engines, state machines, or coordination systems &mdash; ideally in a multi-agent or fleet context</p></li><li><p>
Experience building operator-facing tooling: dashboards, authoring UIs, or systems that translate human intent into structured actions</p></li><li><p>
Exposure to LLM-based agentic systems, particularly using AI to generate or modify structured representations from natural language</p></li><li><p>
Experience integrating with third-party enterprise systems (WMS, ERP, or similar)</p></li><li><p>
Background in robotics or real-time systems where execution state and side-effects need to be managed carefully</p></li></ul><p></p><h1 class="jobSectionHeader"><b>
What We Offer</b></h1><ul><li><p>
Competitive equity: stock options with meaningful upside as we scale.</p></li><li><p>
30+ days off, including 23 days annual leave, all UK bank holidays, and additional company closure days (including Christmas&ndash;New Year shutdown).</p></li><li><p>
Private healthcare, including virtual and in-person care.</p></li><li><p>
Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.</p></li><li><p>
Free daily breakfast, catered lunch, and snacks in-office.</p></li><li><p>
Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.</p></li><li><p>
Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.</p></li></ul></div>

Software Engineer - Workflow Authoring & Deployment

<div><p>Here at Humanoid, we believe in a future where robots amplify human potential. That&rsquo;s why we&rsquo;ve set out on a mission to build the world&rsquo;s most capable, commercially-scalable, and safe humanoid robots. We&rsquo;re bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we&rsquo;re growing the team to take it even further.</p><p></p><h1 class="jobSectionHeader"><b>
About the Role</b></h1><p>
We are looking for a Software Engineer to own the build system and CI infrastructure that every engineer at Humanoid depends on every day. This is foundational work: a slow, unreliable, or opaque build pipeline is a tax on the entire engineering organisation, and getting it right directly determines how fast we can ship robots.</p><p>
We are investing heavily in build infrastructure - hermetic, incremental, fully cached builds across a complex multi-target monorepo spanning firmware, robot software, simulation, and cloud - and we need someone to drive that work and own the system it produces.</p><p>
This is a deeply technical infrastructure role. You will work closely with every engineering team in the organisation, and the quality of your work will be felt by every person who opens a PR.</p><p></p><h2 class="jobSectionHeader"><b>
What You&rsquo;ll Do</b></h2><ul><li><p>
Build and maintain CI pipelines in GitHub Actions: incremental test selection based on affected targets, nightly full builds, and clear triage tooling when main goes red</p></li><li><p>
Instrument the build: CI telemetry, dashboards showing build and test times broken down by job type, branch, and author &mdash; so we stop flying blind on build health</p></li><li><p>
Define and enforce the policies that keep main green: merge queue configuration, PR gating, and the on-call process when broken builds block other engineers</p></li><li><p>
Own and maintain the remote build cache infrastructure, ensuring cache correctness, invalidation on environment changes, and read-only promotion from main only</p></li><li><p>
Own the developer environment story &mdash; local builds, dependency management, and the tooling that lets engineers iterate quickly without fighting their environment</p></li><li><p>
Maintain and evolve the dependency mirroring infrastructure (apt, PyPI, and other upstream registries) so that external package availability never blocks a build</p></li></ul><h2 class="jobSectionHeader"><b><br>
What We&rsquo;re Looking For</b></h2><ul><li><p>
Solid experience with build systems - ideally Bazel, but deep knowledge of CMake or similar is fine; the instincts matter more than the specific tool</p></li><li><p>
Experience designing and operating CI pipelines at scale: incremental testing, artifact caching, runner management, and keeping feedback loops short</p></li><li><p>
Strong understanding of hermetic build environments</p></li><li><p>
Comfort debugging complex build failures across multiple languages and toolchains</p></li><li><p>
Experience with dependency management and the tradeoffs between reproducibility, speed, and upstream risk</p></li><li><p>
Good instincts for developer experience</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Nice To Have</b></h2><ul><li><p>
Familiarity with ROS/ROS2 build tooling (colcon, ament, CMake)</p></li><li><p>
Familiarity with Kubernetes: self-hosted runners, ARC</p></li><li><p>
Experience with GitHub Actions at scale</p></li><li><p>
Background in robotics or embedded systems where build artifacts span multiple target architectures and deployment environments</p></li></ul><p></p><h1 class="jobSectionHeader"><b>
What We Offer</b></h1><ul><li><p>
Competitive equity: stock options with meaningful upside as we scale.</p></li><li><p>
30+ days time off, including 23 days annual leave, all UK bank holidays, and additional company closure days (including Christmas&ndash;New Year shutdown).</p></li><li><p>
Private healthcare, including virtual and in-person care.</p></li><li><p>
Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.</p></li><li><p>
Free daily breakfast, catered lunch, and snacks in-office.</p></li><li><p>
Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.</p></li><li><p>
Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.</p></li></ul></div>

Platform Engineer - Build and CI

Winston Fox

<div>
 <p>
  Amazing opportunity to join the cutting-edge AI team at a top 10 Global Hedge Fund.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Role
 </p>
 <ul>
  <li>
   Design and build robust and scalable AI-powered solutions and workflows for the business.
  </li>
  <li>
   Understand different investment teams' processes and identify opportunities for AI integration or workflow improvements.
  </li>
  <li>
   Develop best practices and standards for applied AI.
  </li>
  <li>
   Ensure your solutions are effective and create tangible value for the investment teams.
  </li>
  <li>
   Supporting, monitoring, and continuously improving existing AI systems and applications.
  </li>
  <li>
   Identifying opportunities to enhance the core AI platform and contributing to the shared libraries and frameworks.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Requirements
 </p>
 <ul>
  <li>
   5-10 years of professional experience implementing AI and machine learning systems in financial markets
  </li>
  <li>
   Demonstrable modelling, agent development, and model training experience with high business impact, i.e. revenue generation or loss implications
  </li>
  <li>
   Broad technical knowledge and a demonstrable passion for learning new technologies and their practical application to business problems.
  </li>
  <li>
   Demonstrable obsession with generative AI and a passion for staying current with the latest developments.
  </li>
  <li>
   A love for automation and continual improvement, with a track record of identifying high-value big-ticket automation opportunities.
  </li>
  <li>
   Exceptional interpersonal and communication skills, with a proven ability to build positive, collaborative relationships with both technical and non-technical colleagues.
  </li>
  <li>
   Exceptional and proven problem-solving and debugging skills.
  </li>
  <li>
   Excellent academic achievements in Computer Science, AI, and Machine Learning.
  </li>
  <li>
   Native level English language skills - verbal and written
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Technologies
 </p>
 <ul>
  <li>
   Coding in Python / C# / Scala / Java / Go
  </li>
  <li>
   Data storage and manipulation tools such as SQL, Pandas/Polars, Snowflake, Vector DBs
  </li>
  <li>
   Generative AI libraries, frameworks and tools such as LangChain, Llamaindex, Aider, Claude Code
  </li>
  <li>
   Best practices and approaches to model performance and benchmarking, including tools like MLFlow
  </li>
  <li>
   Containerisation and orchestration technologies like Docker / Kubernetes / Helm / Flux
  </li>
  <li>
   Data visualisation tools and notebooking tools such as Marimo / Jupyter
  </li>
  <li>
   ETL/ELT technologies such as Airflow / Dagster / DBT
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Offered
 </p>
 <p>
  World-class tech environment, culture and infrastructure, working on cutting-edge projects
 </p>
 <p>
  Work on solutions with clear, direct business and team PnL impact
 </p>
 <p>
  &pound;150k to &pound;250k base salary PA
 </p>
 <p>
  Annual performance bonus 1x - 4x base salary
 </p>
 <p>
  No expense spared benefits package
 </p>
 <p>
  4 days onsite + 1 day wfh
 </p>
 <p>
  Relocation and visa available for "Exceptional" candidates with direct experience
 </p>
 <p>
 </p>
</div>


Generative AI Engineer

algo1

<div>
 <strong>
  About Algo1
  <br/>
  <br/>
 </strong>
 We&rsquo;re a VC-backed stealth-mode company building behavioural AI solutions for the retail industry. Our platform is designed from the ground up &mdash; no legacy, no patchwork systems &mdash; just a clean slate and a clear vision. Our mission is to bring the intelligence of modern machine learning directly to the in-store shopping experience.
 <br/>
 <br/>
 <strong>
  The Role
  <br/>
  <br/>
 </strong>
 You will be an expert in agentic development familiar with both the latest advancements in models as well as the agentic toolchain and best practices. You will work closely with product, design, mobile, and machine learning team members to design &amp; build agents that drive everything from user experience to platform automation and efficiency. Alongside product development, you will bring your expertise to enable the rest of the company to deliver faster and more effectively, whilst maintaining quality, using the latest agentic approaches and tools.
 <br/>
 <br/>
 <strong>
  What You Will Own
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Defining and implementing complex, high-impact agentic AI platform solutions.
  </li>
  <li>
   Driving best practices and enablement for agentic development across the engineering organization.
  </li>
  <li>
   Establishing and maintaining robust evaluation (Evals) strategies for LLM agents, focusing on performance, latency, quality, and explainability.
  </li>
  <li>
   Keeping up with the latest developments in models (Frontier Labs and Open Source) as well as agent development toolchains and best practices.
  </li>
  <li>
   Deployment, scaling, monitoring, and cost-efficiency of agentic applications.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Essential Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Deep understanding and hands-on experience with modern agentic development frameworks (e.g. Pydantic AI).
  </li>
  <li>
   Familiarity with designing and implementing complex, multi-step agentic workflows and planning/reasoning capabilities.
  </li>
  <li>
   Proven ability to design and implement robust evaluation (Evals) strategies for large language model (LLM) agents, including metrics for performance, latency, and quality.
  </li>
  <li>
   Expertise in advanced context management techniques, including retrieval-augmented generation (RAG), memory structures, and context window optimization
  </li>
  <li>
   Experience with deploying and monitoring agentic applications in production environments including scaling, monitoring (OTEL), cost, and token usage.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice to Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience in backend development and event-driven architecture
  </li>
  <li>
   Our stack includes Python, FastAPI, postgres, Kafka and MQTT
  </li>
  <li>
   Worked with IoT or Edge-oriented architectures
  </li>
  <li>
   Experience or knowledge in retail POS, inventory, or loyalty systems
   <br/>
   <br/>
  </li>
 </ul>
 If you&rsquo;re excited by the idea of shaping the future of retail and eager to make a real impact from day one, we&rsquo;d love to hear from you.
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Staff AI Engineer

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