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Staff AI Research Engineer - ML Engineering

Pay
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Work setting
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Employment
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What you’ll work on

Full posting
  • Extend PyTorch-based deep learning frameworks to make them efficient and easy to use

  • Scale infrastructure and tooling for faster, larger distributed training

  • Design data strategy for large datasets and efficient storage so GPUs stay busy

From the employer’s posting
Extend our highly integrated deep learning frameworks (built on top of PyTorch), making them efficient and easy to use for a wide range of use cases.
Scale our current infrastructure and tooling stack to support faster and larger distributed training.
Design data strategy to support large scale datasets and efficient storage, ensuring GPUs stay warm.

What you’ll bring

All qualifications

Core experience

  • MSc or PhD in Computer Science or STEM field focused on ML and deep learning
  • Strong Python skills and fluency with PyTorch, JAX, or TensorFlow
  • Experience writing custom layers, loss functions, and distributed training loops
  • Experience debugging production ML pipelines
  • Clear communicator who can explain complex theory and contribute to engineering culture
Qualification wording
Hold an MSc or PhD in Computer Science or STEM field, with a focus on Machine Learning and Deep Learning.
Have strong software engineering skills in Python and fluency with modern DL frameworks (PyTorch/JAX/TensorFlow).
You don’t just import libraries; you are comfortable writing custom layers, loss functions, and distributed training loops.
You have debugged production ML pipelines
Are a clear communicator who can build from complex theoretical concepts and contribute to the company's internal engineering culture.
Education & alternatives
You should apply if you: - Hold an MSc or PhD in Computer Science or STEM field, with a focus on Machine Learning and Deep Learning. - Have strong software engineering skills in Python and fluency with modern DL frameworks (PyTorch/JAX/TensorFlow). You don’t just import libraries; you are comfortable writing custom layers, loss functions, and distributed training loops.

Benefits in the posting

Full benefits wording
  • Competitive salary and VSOP options
  • Relocation support: up to €2,500 and 4 weeks temporary accommodation
  • Learning: €500/£450 yearly allowance
  • Health & wellness: gym membership and mental health support (Nilo.health)
  • Enhanced parental leave: 22 weeks fully paid for primary caregivers & 6 weeks for secondary caregivers
  • Family support: 5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work
  • A hands-on onboarding program (affectionately labelled “AI-duction”), in which you will be familiarising yourself with our tools and ML pipelines used across the company. This is your opportunity to learn our tech stack, explore the company, and learn how we get things done - all whilst working with other AI and engineering teams from day one
  • Helsing is an equal opportunities employer. We are committed to equal employment opportunity regardless of race, religion, sexual orientation, age, marital status, disability or gender identity. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation.

From the employer’s posting.

About Helsing

Our mission is to protect our democracies.

In the employer’s words · Read in context

Apply at Helsing

Posting record

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Open 6 monthsWe first saw this posting 207 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Apr 14, 2026207 days ago
Recorded sightings
245
Last seen by us
Nov 7, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 207

Up longer than most. Similar jobs usually come down between day 7 and day 71.

From 4,684 similar postings that came down. Coming down is not always a hire.

Helsing is hiring

3 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • 33% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Kubernetes
  • PyTorch
  • TensorFlow
Where the posting names them
- Hold an MSc or PhD in Computer Science or STEM field, with a focus on Machine Learning and Deep Learning. - Have strong software engineering skills in Python and fluency with modern DL frameworks (PyTorch/JAX/TensorFlow). You don’t just import libraries; you are comfortable writing custom layers, loss functions, and distributed training loops. - Are a clear communicator who can build from complex theoretical concepts and contribute to the company's internal engineering culture.
- You have worked with large-scale datasets made of different modalities. Understanding the tradeoffs in locality, encoding, formats, and streaming strategies. - You are proficient with workload orchestrators like Slurm, Kubernetes, or Ray, having used them to schedule and manage complex, concurrent training jobs at scale. - You understand GPU architecture at a low level: memory hierarchies, warp execution, and what makes a GPU suited for training versus inference workloads.
What you will do: - Extend our highly integrated deep learning frameworks (built on top of PyTorch), making them efficient and easy to use for a wide range of use cases. - Scale our current infrastructure and tooling stack to support faster and larger distributed training.

Your next step

Complete your application on helsing.ai. The employer’s form will show what is required.

Applying through Greenhouse

  • No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
  • Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.

Already applied? Track this application

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 624, the most 1,094, and the latest week had 868.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Who we are

Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards.

As democracies, we believe we have a special responsibility to be thoughtful about the development and deployment of powerful technologies like AI. We take this responsibility seriously.

We are an ambitious and committed team of engineers, AI specialists and customer-facing programme managers. We are looking for mission-driven people to join our European teams – and apply their skills to solve the most complex and impactful problems. We embrace an open and transparent culture that welcomes healthy debates on the use of technology in defence, its benefits, and its ethical implications.

The role

At Helsing, we are pioneering the future of autonomous decision-making for defence. Our work spans the full AI landscape, including high-volume data processing, RL agent training, and large-scale foundation models. As a member of a cross-functional team, you will architect and implement the tools and platforms that enable these breakthroughs. Your focus will be on abstracting complex distributed systems to maximise training throughput and developer velocity. We are looking for engineers who can navigate the convergence of machine learning and systems engineering to build robust, scalable platforms.

What you will do:

  • Extend our highly integrated deep learning frameworks (built on top of PyTorch), making them efficient and easy to use for a wide range of use cases.

  • Scale our current infrastructure and tooling stack to support faster and larger distributed training.

  • Design data strategy to support large scale datasets and efficient storage, ensuring GPUs stay warm.

You should apply if you:

  • Hold an MSc or PhD in Computer Science or STEM field, with a focus on Machine Learning and Deep Learning.

  • Have strong software engineering skills in Python and fluency with modern DL frameworks (PyTorch/JAX/TensorFlow). You don’t just import libraries; you are comfortable writing custom layers, loss functions, and distributed training loops.

  • Are a clear communicator who can build from complex theoretical concepts and contribute to the company's internal engineering culture.

  • Have a "first-principles" mindset: you enjoy reading the latest AI optimisation blog posts and integrating them into codebases rapidly.

  • You have debugged production ML pipelines and can tell a good war story about finding a subtle numerical or performance issue.

Note: We operate at an intersection where women, as well as other minority groups, are systematically under-represented. We encourage you to apply even if you don’t meet all the listed qualifications; ability and impact cannot be summarised in a few bullet points.

Nice to have

  • You have hands-on experience training models on large-scale GPU clusters, implementing advanced parallelism strategies, and understanding the underlying cross-node communication patterns (NCCL, MPI).

  • You have worked with large-scale datasets made of different modalities. Understanding the tradeoffs in locality, encoding, formats, and streaming strategies.

  • You are proficient with workload orchestrators like Slurm, Kubernetes, or Ray, having used them to schedule and manage complex, concurrent training jobs at scale.

  • You understand GPU architecture at a low level: memory hierarchies, warp execution, and what makes a GPU suited for training versus inference workloads.

Join Helsing and work with world-leading experts in their fields

  • Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns. 

  • The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world. 

  • Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defence industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward. 

  • In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts.  

  • We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practise responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn’t work, and to take ownership of aspects of our culture that you care deeply about. 

What we offer

  • Competitive salary and VSOP options

  • Relocation support: up to €2,500 and 4 weeks temporary accommodation

  • Learning: €500/£450 yearly allowance

  • Health & wellness: gym membership and mental health support (Nilo.health)

  • Social: regular company events and monthly social allowances

  • Enhanced parental leave: 22 weeks fully paid for primary caregivers & 6 weeks for secondary caregivers

  • Family support: 5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work
  • A hands-on onboarding program (affectionately labelled “AI-duction”), in which you will be familiarising yourself with our tools and ML pipelines used across the company. This is your opportunity to learn our tech stack, explore the company, and learn how we get things done - all whilst working with other AI and engineering teams from day one

These are the core benefits across all locations, there may be additional benefits in certain locations.


Helsing is an equal opportunities employer. We are committed to equal employment opportunity regardless of race, religion, sexual orientation, age, marital status, disability or gender identity. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation. 

#LI-FH1
 
Helsing's Candidate Privacy and Confidentiality Regime can be found here. 
 
 
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Location & working pattern

Berlin; London; Munich

- Enhanced parental leave: 22 weeks fully paid for primary caregivers & 6 weeks for secondary caregivers - Family support: 5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work - A hands-on onboarding program (affectionately labelled “AI-duction”), in which you will be familiarising yourself with our tools and ML pipelines used across the company. This is your opportunity to learn our tech stack, explore the company, and learn how we get things done - all whilst working with other AI and engineering teams from day one
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