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Senior Machine Learning Engineer

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AI Summary

We are hiring a Senior Machine Learning Engineer to lead the design, training, and deployment of ML systems in production. The role combines deep ML expertise with strong software engineering, owning models from research through scaled inference. Key requirements include 5+ years of experience, strong Python skills, and deep experience with PyTorch or TensorFlow.

Key Highlights
Lead design, training, and deployment of ML systems in production
5+ years of experience in machine learning engineering with production ownership
Fully remote, flexible work hours with competitive compensation
Key Responsibilities
Design, train, and deploy machine learning models at production scale
Lead architecture decisions for training, evaluation, and inference pipelines
Build evaluation frameworks and monitoring for model quality and drift
Partner with data engineering on training data pipelines and feature stores
Mentor junior ML engineers and contribute to ML practice
Stay current on research and bring proven techniques into production
Technical Skills Required
Python PyTorch Cloud ML Infrastructure
Benefits & Perks
Competitive salary with indicative range $150,000 – $250,000
Fully remote, flexible work hours
Performance-based bonus structure and annual learning & development stipend

Job Description


  • Role: Senior Machine Learning Engineer
  • Location: Remote
  • Employment Type: Full-time


Compensation: Competitive salary commensurate with experience, qualifications, and location. Indicative range: $150,000 – $250,000 (USD equivalent), plus benefits.



Role Overview

We are hiring a Senior Machine Learning Engineer to lead the design, training, and deployment of ML systems in production. The role combines deep ML expertise with strong software engineering — owning models from research through scaled inference.


Key Responsibilities

- Design, train, and deploy machine learning models at production scale

- Lead architecture decisions for training, evaluation, and inference pipelines

- Build evaluation frameworks and monitoring for model quality and drift

- Partner with data engineering on training data pipelines and feature stores

- Mentor junior ML engineers and contribute to ML practice

- Stay current on research and bring proven techniques into production


Required Skills and Qualifications

- 5+ years in machine learning engineering with production ownership

- Strong Python skills and deep experience with PyTorch or TensorFlow

- Experience training and serving models at scale (deep learning, LLMs, or classical ML)

- Hands-on with cloud ML infrastructure (AWS Sagemaker, GCP Vertex, Databricks, or similar)

- Strong software engineering fundamentals (testing, code review, system design)

- Track record of shipping ML systems that delivered measurable business value


What You'll Bring

- Curiosity about how models behave and why they fail

- Rigor in following guidelines and flagging ambiguity early

- Strong written communication, including ability to document findings clearly

- Comfort working asynchronously across time zones


What We Offer

- Fully remote, flexible work hours

- Performance-based bonus structure

- Annual learning & development stipend

- Health and wellness benefits (varies by location)

- Opportunity to work on high-scale, real-world impact projects


Equal Opportunity Statement

This is an equal opportunity role. Applications are welcomed from all qualified individuals regardless of race, color, ethnicity, nationality, gender, gender identity or expression, sexual orientation, age, religion, disability, marital status, or any other characteristic protected by applicable law. All hiring decisions are based solely on qualifications, skills, and demonstrated ability.


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