Member of Technical Staff, Machine Learning

Protingent

Washington

Hybrid

USD 120,000 - 210,000

Full time

14 days+

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Job summary

Protingent Staffing seeks a Member of Technical Staff, Machine Learning for a fully remote role with our client. You will build core ML components and work on real production systems from day one, shipping and iterating on models in production.

You will collaborate with senior ML engineers and product teams to ensure models meet accuracy, latency, and reliability targets while managing data pipelines for real-world and synthetic data.

Qualifications

  • Strong foundations in machine learning and modern neural architectures.
  • Additional hands-on ML experience is desirable.
  • Experience with production ML pipelines is a plus.

Responsibilities

  • 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.
  • Ensure ML models in production meet accuracy, latency, and reliability targets.
  • Identify, debug, and address production issues quickly with root-cause analysis.
  • Ensure pipelines, training loops, and inference systems are robust and maintainable.
  • Collaborate with engineers, product, and research teams to deliver ML-powered features.
  • Drive iterations on models and systems using real-world signals.

Skills

ML fundamentals
Hands-on ML training
Production code
Learning agility
Ambiguity resilience
Shipping mindset
Python, PyTorch/JAX, GPUs

Job description

Member of Technical Staff, Machine Learning

Protingent Staffing has an exciting direct hire Member of Technical Staff, Machine Learning with our client that is fully remote.

Job Description

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.

Responsibilities
  • 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; ensure ML models in production meet expected accuracy, latency, and reliability targets.
  • Identify, debug, and address production issues quickly with effective root‑cause analysis.
  • Ensure data pipelines, training loops, and inference systems are robust, reproducible, and maintainable.
  • Collaborate effectively with engineers, product, and research teams to deliver reliable ML‑powered features.
  • Drive iterations on models and systems using real‑world signals and measurable improvements.
Qualifications
  • 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.
  • Must have experience with Python, PyTorch/JAX, and production‑ML systems running on GPUs.
Job Details
  • Job Type: Direct Hire
  • Pay Range: Market Rate
  • Location: Fully Remote
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