Remote Software Engineer - Distributed ML Training - Gensyn
Remote Software Engineer - Distributed ML Training - Gensyn

Remote Software Engineer - Distributed ML Training - Gensyn

London Full-Time 36000 - 60000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Design and implement systems for ML execution and optimise training algorithms.
  • Company: Gensyn is revolutionising machine learning compute, making it accessible to everyone.
  • Benefits: Enjoy fully remote work, competitive salary, equity, and annual company retreats.
  • Why this job: Join a small, innovative team driving the future of AI with autonomy and direct impact.
  • Qualifications: Experience in distributed model training, networking, and open source contributions required.
  • Other info: Willingness to learn Rust is essential; enjoy a culture of extreme learning and ownership.

The predicted salary is between 36000 - 60000 ÂŁ per year.

The world will be unrecognisable in 5 years. Machine learning models are driving our cars, testing our eyesight, detecting our cancer, giving sight to the blind, giving speech to the mute, and dictating what we consume, enjoy, and think. These AI systems are already an integral part of our lives and will shape our future as a species. Soon, we'll conjure unlimited content: from never-ending TV series (where we’re the main character) to personalised tutors that are infinitely patient and leave no student behind. We’ll augment our memories with foundation models—individually tailored to us through RLHF and connected directly to our thoughts via Brain-Machine Interfaces—blurring the lines between organic and machine intelligence and ushering in the next generation of human development. This future demands immense, globally accessible, uncensorable, computational power. Gensyn is the machine learning compute protocol that translates machine learning compute into an always-on commodity resource—outside of centralised control and as ubiquitous as electricity—accelerating AI progress and ensuring that this revolutionary technology is accessible to all of humanity through a free market.

Our Principles:

  • AUTONOMY: Don’t ask for permission - we have a constraint culture, not a permission culture. Claim ownership of any work stream and set its goals/deadlines, rather than waiting to be assigned work or relying on job specs. Push & pull context on your work rather than waiting for information from others and assuming people know what you’re doing. No middle managers - we don’t (and will likely never) have middle managers.
  • FOCUS: Small team - misalignment and politics scale super-linearly with team size. Small protocol teams rival much larger traditional teams. Thin protocol - build and design thinly. Reject waste - guard the company’s time, rather than wasting it in meetings without clear purpose/focus, or bikeshedding.
  • REJECT MEDIOCRITY: Give direct feedback to everyone immediately rather than avoiding unpopularity, expecting things to improve naturally, or trading short-term pain for long-term pain. Embrace an extreme learning rate rather than assuming limits to your ability/knowledge. Drive ownership to final outcome, despite barriers.

Responsibilities:

  • Design and implement systems for orchestration of ML execution—enabling training across our decentralised and heterogeneous infrastructure.
  • Performance optimisation—continually profile and optimise our training algorithms.
  • Implement novel research—develop mechanisms and algorithms to tackle new problems.
  • Engineering support—collaborate on wider ML issues (e.g., reproducible training).
  • Write & engage—contribute to technical reports and papers, and discuss with the community.

Minimum requirements:

  • Hands-on experience with distributed foundation model training, designing or working with large cluster training systems.
  • Networking expertise—understanding and troubleshooting protocols like IP, TCP, UDP, HTTP; experience with NCCL, GLOO, MPI.
  • Open source experience—contributing to large codebases as maintainer or trusted contributor.
  • Willingness to learn Rust—since we are a Rust-based company, familiarity or readiness to learn is essential.
  • Computer science background—knowledge of algorithms, data structures, and computational complexity.
  • Self-motivated with excellent communication skills.
  • Comfortable working in an autonomous, research environment with unpredictable timelines.

Nice to haves:

  • Experience in systems programming in Rust (knowledge of lifetimes, Pin, etc.).
  • Research background in distributed systems or ML domains.
  • Understanding of blockchain fundamentals.

Compensation / Benefits:

  • Competitive salary, equity, and tokens.
  • Fully remote work —we hire between West Coast (PT) and Central Europe (CET) time zones.
  • Relocation assistance —available for those moving after hiring.
  • Annual company retreats —4 fully paid trips worldwide.
  • Equipment, paid sick leave, private health, vision, dental insurance —including dependents.

Remote Software Engineer - Distributed ML Training - Gensyn employer: Gensyn

Gensyn is an exceptional employer for Remote Software Engineers, offering a unique opportunity to work at the forefront of machine learning technology in a fully remote environment. With a strong emphasis on autonomy and ownership, employees are encouraged to take initiative and drive their projects forward without the constraints of middle management. The company fosters a culture of continuous learning and innovation, providing competitive salaries, equity options, and comprehensive benefits, including annual retreats and health insurance for dependents, making it an attractive place for those seeking meaningful and rewarding employment.
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Contact Detail:

Gensyn Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Remote Software Engineer - Distributed ML Training - Gensyn

✨Tip Number 1

Familiarise yourself with the latest trends in distributed machine learning and the technologies used in this field. Being well-versed in protocols like NCCL, GLOO, and MPI will give you an edge during discussions and interviews.

✨Tip Number 2

Engage with the open-source community by contributing to relevant projects. This not only showcases your skills but also demonstrates your commitment to collaborative work, which is highly valued at Gensyn.

✨Tip Number 3

Brush up on your Rust programming skills, as familiarity or a willingness to learn Rust is essential for this role. Consider building small projects or contributing to existing ones to gain practical experience.

✨Tip Number 4

Prepare to discuss your previous experiences with performance optimisation and algorithm development. Be ready to share specific examples of how you've tackled challenges in these areas, as this aligns closely with the responsibilities of the role.

We think you need these skills to ace Remote Software Engineer - Distributed ML Training - Gensyn

Distributed Machine Learning
Cluster Training Systems
Networking Protocols (IP, TCP, UDP, HTTP)
NCCL
GLOO
MPI
Open Source Contribution
Rust Programming
Algorithms
Data Structures
Computational Complexity
Self-Motivation
Excellent Communication Skills
Autonomous Work Environment
Research Skills

Some tips for your application 🫡

Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Remote Software Engineer position at Gensyn. Familiarise yourself with their principles and the technologies they use, especially in distributed ML training.

Tailor Your CV: Customise your CV to highlight relevant experience in distributed systems, networking protocols, and any open-source contributions. Emphasise your hands-on experience with large cluster training systems and your willingness to learn Rust.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for machine learning and your alignment with Gensyn's principles. Discuss specific projects or experiences that demonstrate your ability to work autonomously and your commitment to rejecting mediocrity.

Showcase Your Communication Skills: In your application, provide examples of how you've effectively communicated complex technical concepts in the past. This is crucial as the role requires excellent communication skills and collaboration on wider ML issues.

How to prepare for a job interview at Gensyn

✨Showcase Your Technical Skills

Be prepared to discuss your hands-on experience with distributed foundation model training and large cluster systems. Bring examples of past projects where you've optimised performance or implemented novel research, as this will demonstrate your capability in the role.

✨Emphasise Autonomy and Ownership

Gensyn values a culture of autonomy, so highlight instances where you've taken ownership of projects. Discuss how you set goals, pushed for context, and drove outcomes without waiting for direction, showcasing your self-motivation and proactive approach.

✨Demonstrate Communication Skills

Since collaboration is key in a small team environment, be ready to illustrate your communication skills. Share experiences where you effectively engaged with others, contributed to technical discussions, or provided direct feedback, as this aligns with their principles.

✨Express Willingness to Learn

Gensyn is looking for candidates who are eager to learn, especially in Rust. Be honest about your current knowledge and express your enthusiasm for picking up new skills. This shows that you're adaptable and ready to grow within the company.

Remote Software Engineer - Distributed ML Training - Gensyn
Gensyn
Location: London

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