Member of Technical Staff, Machine Learning

Sarsfield Group; United States; Remote; USD 145.000 - 220.000; Vollzeit

Benefits dieser Stelle

Health and Dental

Life insurance

401(k) matching

Equity

Zusammenfassung

Sarsfield Group is seeking a Member of Technical Staff, Machine Learning to build core ML components and deploy production-grade models. You will work on real systems from day one, shipping, debugging, and iterating under production constraints.

The role emphasizes scaling models, improving data pipelines, and collaborating with engineers, product, and research teams to deliver reliable ML-powered features in a remote US/Canada setup.

Qualifikationen

• Strong foundations in machine learning and modern neural architectures.
• Some hands-on experience training, fine-tuning, or deploying ML models.
• Comfortable writing production-quality code and learning new tools quickly.
• Curious, coachable, and eager to learn from real systems in production.

Aufgaben

• Build and improve ML components across data, training, evaluation, and inference.
• Fine-tune and adapt models as part of larger production systems.
• Implement evaluation and testing to understand model behavior.
• Help build and maintain data pipelines for real-world and synthetic data.
• Debug model issues, performance problems, and production incidents.
• Ship improvements iteratively and learn from real user feedback.
• Work closely with senior ML engineers and product teams.
• Work under real production constraints: latency, cost, reliability, and safety

Kenntnisse

Python

ML model development

PyTorch

JAX

Tools

PyTorch

JAX

Jobbeschreibung

Member of Technical Staff, Machine Learning

Member of Technical Staff, Machine Learning

Remote: US/Canada

About Our Client

Founded in 2019, we’re the leading insurance platform in Southeast Asia, helping millions of people find the best-value coverage online. Now we’re expanding into saving, investing, spending and more, all with one goal: helping people get more from their money every day. Join our diverse, global team and help make financial services simpler for everyone.

There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they’re not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal to no prompting.

Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. We believe products will greatly reduce hallucinations.

Our objective is to organise anyone’s life, allowing us all to spend time on valuable and meaningful things.

About the Role

As a Member of Technical Staff, Machine Learning, you will build core ML components. You will work on real production systems from day one, learning how large-scale ML behaves outside of research settings.

This role is for engineers who want to develop strong systems judgment by shipping, debugging, and iterating on real-world ML.

Focus

Build and improve ML components across data, training, evaluation, and inference.

Fine-tune and adapt models as part of larger production systems.

Implement evaluation and testing to understand model behavior.

Help build and maintain data pipelines for real-world and synthetic data.

Debug model issues, performance problems, and production incidents.

Ship improvements iteratively and learn from real user feedback.

Work closely with senior ML engineers and product teams.

Work under real production constraints: latency, cost, reliability, and safety

Python

PyTorch / JAX

Production ML systems running on GPUs

Ideal Experience

Strong foundations in machine learning and modern neural architectures.

Some hands-on experience training, fine-tuning, or deploying ML models.

Comfortable writing production-quality code and learning new tools quickly.

Curious, coachable, and eager to learn from real systems in production.

Able to work through ambiguity with guidance and grow ownership over time.

Bias toward shipping, iteration, and continuous improvement.

Outcomes

ML models in production meet expected accuracy, latency, and reliability targets.

Production issues are identified quickly, debugged effectively, and root causes addressed.

Data pipelines, training loops, and inference systems are robust, reproducible, and maintainable.

Collaborates effectively with engineers, product, and research teams to deliver reliable ML-powered features.

Iterations on models and systems are driven by real-world signals and measurable improvements.

How We Work

The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product

Compensation:

US: $145,000 – $220,000 USD

CAD: $135,000 – $185,000 CAD

US: Health and Dental, Life insurance, 401(k) matching, and equity

Canada: Health and Dental, Life Insurance, equity

We thank all applicants for their interest; however, only those selected for an interview will be contacted.