What Jobs are available for Machine Learning Developer in the United Kingdom?

Humanoid is the first AI and robotics company in the UK, creating the world’s most advanced, reliable, commercially scalable, and safe humanoid robots. Our first humanoid robot HMND 01 is a next-gen labour automation unit, providing highly efficient services across various use cases, starting with industrial applications.

Our Mission

At Humanoid we strive to create the world’s leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into daily life and amplify human capacity.

Vision

In a world where artificial intelligence opens up new horizons, our faith in its potential unveils a new outlook where, together, humans and machines build a new future filled with knowledge, inspiration, and incredible discoveries. The development of a functional humanoid robot underpins an era of abundance and well-being where poverty will disappear, and people will be able to choose what they want to do. We believe that providing a universal basic income will eventually be a true evolution of our civilization.

Solution

As the demands on our built environment rise, labour shortages loom. With the world’s workforce increasingly moving away from undesirable tasks, the manufacturing, construction, and logistics industries critical to our daily lives are left exposed. By deploying our general-purpose humanoid robots in environments deemed hazardous or monotonous, we envision a future where human well-being is safeguarded while closing the gaps in critical global labour needs.

What You'll Do:

• Train policies via representation learning, behaviour cloning and RL; own the full loop from data to deployment.
• Partner with teleoperations to drive data collection: specify what “good” looks like, ensure diversity/coverage, and close the gap between sim and real.
• Run pre-/mid-/post-training on multimodal LLM/VLM/VLA stacks; plug in new modalities (vision, audio, proprioception, LiDAR/point clouds, …) without breaking existing ones.
• Build and maintain continuous pipelines: ingest simulation + tele‑op logs, version them, apply weak‑supervision labelling, curate balanced datasets, and auto‑surface fresh failure cases into retraining.
• Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‑time edge inference.

We’re Looking For:

• 3+ years building deep‑learning systems (industry or research) with shipped models or published artifacts to show for it.
• Hands‑on with at least one of: LLMs, VLMs, or image/video generative models — architecture, training, and inference.
• Experience with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training strategies.
• Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code.
• You document experiments clearly and communicate trade‑offs crisply.

Nice-to-Have:

• Robotics or autonomous driving experience.
• RL for LLMs or robotics (PPO, DPO, SAC, etc.).
• Proven productization of deep nets (latency/throughput constraints, telemetry, on‑device optimization).
• Publications at ICLR/ICML/NeurIPS or equivalent open‑source contributions.
• Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open VLA frameworks.

What We Offer:

• Competitive salary plus participation in our Stock Option Plan
• UK Private Insurance
• Paid vacation with adjustments based on your location to comply with local labor laws
• Travel opportunities to our Vancouver and Boston offices
• Office perks: free breakfasts, lunches, snacks, and regular team events
• Freedom to influence the product and own key initiatives
• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics
• Startup culture prioritising speed, transparency, and minimal bureaucracy

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you will add something. Our developer documentation department seeks a creative engineer who has a robust knowledge of large language models (LLMs), generative AI, and experience with code generation. Our ideal candidate has the ability to fine-tune pre-trained models, and work collaboratively in a multi-discipline team. Strong engineering fundamentals and a passion for code generation models are required.

Description

As an Applied ML Engineer in the Developer Publications Intelligence team, you will join a multi-discipline team of passionate engineers to design, fine-tune, and produce models that will be used by existing and future tools produced by Apple for third-party developers. We are looking for exceptional candidates to help define the future of Swift code generation in our tools and beyond. Your role is to ensure Apple and our third-party developers using Xcode deliver extraordinary software products to millions of customers around the world Your duties will include: - Fine-tuning models and making them available for engineers to evaluate and define further experiments - Actively engaging in all aspects of model development, from ideation, training, experimentation to deployment - Collaborating with data collection, model evaluation, and tool integration teams to develop and implement model solutions - Developing and maintaining frameworks and tools to help facilitate the model fine-tuning process.

Minimum Qualifications

• Proficiency using open-source ML toolkits and frameworks (e.g., PyTorch, TensorFlow, OpenNMT)
• Strong programming skills (Python, C/C++, Swift, or other language)
• Experience with Machine Learning, with a particular focus on Large Language Models (LLM) that generate code
• Comprehensive knowledge and hands-on experience with fine-tuning approaches, model recipes, and training models.

Preferred Qualifications

• BS, MS or PhD in Computer Science, Artificial Intelligence, or Machine Learning (or equivalent experience)
• Experience adapting re-trained LLMs for downstream tasks
  Proficiency with Apple's development APIs (SwiftUI, Foundation, etc)

Submit CV

• Design, develop, and implement deep learning models and algorithms.
• Train, evaluate, and optimize deep learning models for performance and accuracy.
• Work with large datasets, ensuring data quality and preparation for model training.
• Deploy deep learning models into production environments.
• Collaborate with researchers and engineers to explore new AI techniques.
• Stay up-to-date with the latest advancements in deep learning and AI research.
• Contribute to the architectural design of AI systems.
• Write clean, efficient, and well-documented code.
• Troubleshoot and resolve issues related to model performance and deployment.

• Master's or Ph.D. in Computer Science, Machine Learning, AI, or a related quantitative field.
• Minimum 5 years of experience in deep learning research and development.
• Strong proficiency in Python and deep learning frameworks (TensorFlow, PyTorch, Keras).
• Expertise in various deep learning architectures (CNNs, RNNs, Transformers, etc.).
• Experience with data preprocessing, feature engineering, and model evaluation.
• Familiarity with big data technologies (e.g., Spark, Hadoop).
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and teamwork abilities.
• A passion for innovation and a strong research mindset.

• Conduct original research in deep learning and related AI fields.
• Develop and implement novel AI algorithms and models.
• Analyze and interpret complex data to derive insights.
• Collaborate with engineers to deploy research prototypes.
• Publish research findings in leading academic venues.
• Stay current with the latest advancements in AI research.
• Contribute to the intellectual property portfolio of the company.
• Present research ideas and results to technical and non-technical audiences.

• PhD in Computer Science, AI, ML, or a related field.
• Demonstrated research experience in deep learning (CNNs, RNNs, Transformers, etc.).
• Proficiency in Python and deep learning frameworks (TensorFlow, PyTorch).
• Strong understanding of machine learning algorithms and statistical modeling.
• Experience with large-scale data processing and analysis.
• Excellent problem-solving and critical thinking skills.
• Strong communication and collaboration abilities in a remote setting.

• Conduct cutting-edge research in deep learning, exploring new architectures, training methodologies, and optimization techniques.
• Design, develop, and implement advanced deep learning models for complex AI applications.
• Collaborate with a world-class team of researchers and engineers on challenging AI projects.
• Publish research findings in top-tier academic conferences and journals.
• Develop and maintain robust, scalable, and efficient AI/ML pipelines for research and deployment.
• Stay abreast of the latest advancements in AI, machine learning, and related fields through continuous learning and literature review.
• Experiment with different algorithms and datasets, analyze results, and draw insightful conclusions.
• Contribute to the intellectual property portfolio through invention disclosures and patent applications.
• Mentor junior researchers and contribute to a collaborative and innovative research environment.
• Present research outcomes and technical details to both technical and non-technical audiences.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a closely related quantitative field.
• A strong publication record in leading AI/ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL).
• Proven expertise in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Deep understanding of fundamental machine learning concepts, algorithms, and statistical modeling.
• Proficiency in programming languages like Python, along with experience in scientific computing libraries (e.g., NumPy, SciPy, Pandas).
• Experience with large-scale datasets and distributed computing environments is a significant plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Exceptional communication and collaboration abilities, essential for a remote research setting.
• Ability to work independently, be self-motivated, and drive research initiatives forward.
• Experience with cloud platforms (AWS, GCP, Azure) for machine learning workloads is advantageous.

• Design, develop, and implement state-of-the-art deep learning models and algorithms for various applications, including computer vision, natural language processing, and predictive analytics.
• Conduct rigorous experimentation and evaluation of models, ensuring high performance, scalability, and robustness.
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to translate business requirements into technical solutions.
• Research and stay abreast of the latest advancements in deep learning, machine learning, and artificial intelligence, identifying opportunities for innovation.
• Develop and maintain efficient data pipelines and MLOps practices for model training, deployment, and monitoring.
• Write clean, well-documented, and maintainable code in Python and relevant deep learning frameworks (e.g., TensorFlow, PyTorch).
• Contribute to the overall AI strategy and roadmap, providing technical leadership and guidance.
• Mentor junior engineers and share knowledge within the team.
• Present research findings and technical designs to both technical and non-technical audiences.
• Troubleshoot and debug complex issues in model training and inference.

• MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Proven track record of at least 5 years in developing and deploying deep learning models in a professional setting.
• Deep understanding of machine learning theory, algorithms, and best practices.
• Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, Keras.
• Experience with cloud platforms (AWS, GCP, Azure) and associated ML services.
• Strong experience with data manipulation, feature engineering, and data visualization techniques.
• Excellent problem-solving skills and the ability to work independently in a remote environment.
• Strong communication and collaboration skills, with the ability to articulate complex technical concepts clearly.
• Experience with MLOps principles and tools (e.g., Docker, Kubernetes, MLflow) is a plus.
• Publications in top-tier AI conferences or journals are highly desirable.

• Lead the design and architecture of advanced deep learning systems and pipelines.
• Develop, train, and optimize state-of-the-art deep learning models for various applications (e.g., NLP, computer vision, reinforcement learning).
• Implement and deploy AI models into production environments, ensuring scalability, performance, and reliability.
• Conduct thorough research into new AI techniques and technologies, evaluating their potential applications.
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate AI solutions.
• Mentor junior AI engineers and contribute to the team's technical growth.
• Stay abreast of the latest research papers, conferences, and industry trends in AI and deep learning.
• Develop and maintain robust MLOps practices for model lifecycle management.
• Author technical documentation, present findings, and share knowledge within the organization.
• Contribute to the company's intellectual property through innovation and patents.

• MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Extensive experience (7+ years) in developing and deploying deep learning models in production.
• Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Strong programming skills in Python and experience with relevant libraries (e.g., NumPy, Pandas, Scikit-learn).
• Deep understanding of machine learning algorithms, statistical modelling, and data structures.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Proven ability to lead complex technical projects and mentor team members.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration skills, with the ability to articulate complex technical concepts.
• Publication record in top-tier AI conferences or journals is a strong plus.

• Lead the design, implementation, and deployment of state-of-the-art deep learning models for various applications.
• Manage and mentor a team of AI engineers and researchers, fostering a collaborative and high-performance environment.
• Define AI strategy and roadmap, aligning technical objectives with business goals.
• Conduct cutting-edge research into new AI techniques and algorithms.
• Develop and optimize deep learning architectures using frameworks such as TensorFlow, PyTorch, or Keras.
• Oversee the entire machine learning lifecycle, from data preprocessing and feature engineering to model training, validation, and deployment.
• Implement MLOps practices to ensure robust and scalable AI systems.
• Collaborate with product teams to integrate AI solutions into client offerings.
• Evaluate and select appropriate datasets and tools for AI projects.
• Present research findings and project outcomes to technical and non-technical stakeholders.
• Stay abreast of the latest advancements in AI, machine learning, and related fields.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 5+ years of hands-on experience in developing and deploying deep learning models.
• Expertise in programming languages such as Python, with strong proficiency in relevant libraries (e.g., NumPy, Pandas, Scikit-learn).
• Deep understanding of deep learning frameworks (TensorFlow, PyTorch, Keras).
• Proven experience with various neural network architectures (CNNs, RNNs, Transformers).
• Experience with distributed training and large-scale datasets.
• Strong knowledge of data structures, algorithms, and software engineering best practices.
• Demonstrated leadership experience in managing technical teams.
• Excellent analytical, problem-solving, and critical thinking skills.
• Superb communication and presentation skills, with the ability to explain complex technical concepts clearly.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies is highly desirable.