ML Research Engineer Job at Recraft (London)

ML Research Engineer, ML Systems

Scale’s ML platform (RLXF) team builds our internal distributed framework for la...

Location

United States , San Francisco; Seattle; New York

Salary:

218400.00 - 273000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

Strong excitement about system optimization
Experience with multi-node LLM training and inference
Experience with developing large-scale distributed ML systems
Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
Strong written and verbal communication skills and the ability to operate in a cross functional team environment

Job Responsibility

Build, profile and optimize our training and inference framework
Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation
Research and integrate state-of-the-art technologies to optimize our ML system

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO
additional benefits such as a commuter stipend
equity based compensation

Fulltime

ML Research Engineer - Hardware Codesign

OpenAI’s Hardware organization develops silicon and system-level solutions desig...

Location

United States , San Francisco

Salary:

185000.00 - 455000.00 USD / Year

OpenAI

Expiration Date

Until further notice

Requirements

Exceptional track record of high-quality technical output
Strong Python, and C++ or Rust
Experience writing Triton, CUDA, or similar
Working knowledge of PyTorch or JAX
Practical understanding of floating point numerics and model quantization
Deep understanding of transformer models
Experience writing RTL (especially for floating point logic) and understanding of PPA tradeoffs is a plus
Strong cross-functional communication

Job Responsibility

Build on our roofline simulator to track evolving workloads
Debug gaps between performance simulation and real measurements
Write emulation kernels for low-precision numerics and lossy compression schemes
Prototype numerics modules by pushing RTL through synthesis
Proactively pull in new ML workloads and prototype them
Understand the whole picture from ML science to hardware optimization
Build ad-hoc collaborations across teams
Communicate design tradeoffs clearly

What we offer

Medical, dental, and vision insurance for you and your family
Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses
401(k) retirement plan with employer match
Paid parental leave
Paid time off
13+ paid company holidays
Mental health and wellness support
Employer-paid basic life and disability coverage
Annual learning and development stipend
Daily meals in our offices, and meal delivery credits

Fulltime

Member of Technical Staff - ML Research Engineer, Data

Our Data team powers Liquid Foundation Models across pre-training, vision, audio...

Location

United States , San Francisco; Boston

Salary:

Not provided

Liquid AI

Expiration Date

Until further notice

Requirements

Strong Python skills with the ability to quickly comprehend problems and translate them into clean, working code
Solid ML fundamentals: experience training, evaluating, and iterating on models (PyTorch preferred)
Track record of learning new technical domains quickly
3+ years relevant experience with an M.S., or 1+ year with a Ph.D. (5+ years with a B.S.)

Job Responsibility

Build and maintain data processing, filtering, and selection pipelines at scale
Create pipelines for pretraining, midtraining, SFT, and preference optimization datasets
Design synthetic data generation systems using LLMs, structured prompting, and domain-specific generators
Design and run evaluations and ablations to measure dataset's impact on model performance
Monitor public datasets across text, vision, and audio domains
Collaborate with pre-training, vision, and audio teams on modality-specific data needs

What we offer

Competitive base salary with equity in a unicorn-stage company
We pay 100% of medical, dental, and vision premiums for employees and dependents
401(k) matching up to 4% of base pay
Unlimited PTO plus company-wide Refill Days throughout the year

Fulltime

Member of Technical Staff - ML Research Engineer, Multi-Modal - Audio

Our Audio team is building frontier speech-language models that handle STT, TTS,...

Location

United States , San Francisco, Boston

Salary:

Not provided

Liquid AI

Expiration Date

Until further notice

Requirements

Strong programming fundamentals with demonstrated ability to write clean, maintainable, production-grade code
Experience building and shipping production ML systems beyond model training (data pipelines, evals, serving infrastructure)
Proficiency in PyTorch and familiarity with distributed training frameworks (DeepSpeed, FSDP, or similar)
Track record of collaborating effectively in shared codebases with high engineering standards

Job Responsibility

Build and scale data pipelines for audio model training, including preprocessing, augmentation, and quality filtering at scale
Design, implement, and maintain evaluation systems that measure multimodal performance across internal and public benchmarks
Fine-tune and adapt audio models for customer-specific use cases, owning delivery from requirements through deployment
Contribute production code to the core audio repository, collaborating with infrastructure and research teams
Support experimentation under real hardware constraints, shifting between customer work and core development as priorities evolve

What we offer

Competitive base salary with equity in a unicorn-stage company
We pay 100% of medical, dental, and vision premiums for employees and dependents
401(k) matching up to 4% of base pay
Unlimited PTO plus company-wide Refill Days throughout the year

Fulltime

AI Research Engineer - ML Engineering

At Helsing, we are pioneering the future of autonomous decision-making for defen...

Location

Germany; United Kingdom , Berlin; Munich; London

Salary:

Not provided

Helsing

Expiration Date

Until further notice

Requirements

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)
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 have debugged production ML pipelines

Job Responsibility

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 we offer

Competitive compensation and stock options
Relocation support
Social and education allowances
Regular company events and all-hands
A hands-on onboarding program

Fulltime

Research Engineer, ML, AI & Computer Vision

The aim of this role is to develop, advance and integrate ML, computer vision mo...

Location

United States , Redmond

Salary:

217000.00 USD / Year ▼

Research Engineer, Core ML

This is a research engineering role with direct production impact. You will tran...

Location

United States , San Francisco

Salary:

200000.00 - 280000.00 USD / Year

Together AI

Expiration Date

Until further notice

Requirements

3+ years of experience working on ML systems, large‑scale model training, inference, or adjacent areas (or equivalent experience via research / open source)
Advanced degree in Computer Science, EE, or a related field, or equivalent practical experience
Demonstrated experience owning complex technical projects end‑to‑end
Strong expertise in at least one of the following: Large‑scale inference systems (e.g., SGLang, vLLM, FasterTransformer, TensorRT, custom engines, or similar), GPU performance, distributed serving
RL / post‑training for LLMs or large models (e.g., GRPO, RLHF/RLAIF, DPO‑like methods, reward modeling)
Model architecture design for Transformers or other large neural nets
Distributed systems / high‑performance computing for ML
Strong coding ability in Python
Experience profiling and optimizing performance across GPU, networking, and memory layers
Track record of impactful work in ML systems, RL, or large‑scale model training (papers, open‑source projects, or production systems)

Job Responsibility

Advance inference efficiency end‑to‑end
Design and prototype algorithms, architectures, and scheduling strategies for low‑latency, high‑throughput inference
Implement and maintain changes in high‑performance inference engines
Profile and optimize performance across GPU, networking, and memory layers
Unify inference with RL / post‑training
Design and operate RL and post‑training pipelines
Make RL and post‑training workloads more efficient with inference‑aware training loops
Co‑design algorithms and infrastructure
Run ablations and scale‑up experiments to understand trade‑offs
Own critical systems at production scale

What we offer

Startup equity
Health insurance
Competitive benefits

Fulltime

Research Engineer, Systems ML - Compilers

We are seeking a software engineer to support the development of the compiler to...

Location

United States , Sunnyvale

Salary:

257000.00 USD / Year ▼

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ML Research Engineer

Job Description

Job Responsibility

Requirements

What we offer

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