Harnham06.02.26
AI SCORE 8.5

Senior Machine Learning Engineer - Remote Opportunity

$180K–$220K/year

About the Role

We are looking for a Senior Machine Learning Engineer to join our team in a fully remote capacity. This role offers a competitive salary of up to $220,000 and the chance to work with cutting-edge technologies in AI and machine learning.

What You'll Do

  • Architect and train neural network models for optimization and audience modeling using PyTorch and distributed training frameworks.
  • Build multi-GPU training pipelines and implement hyperparameter tuning strategies.
  • Develop feature engineering workflows using PySpark and embedding techniques.
  • Own the ML lifecycle from training to batch inference, ensuring automation and reproducibility.
  • Implement monitoring and observability solutions to track model performance and system health.
  • Collaborate with cross-functional teams to align ML initiatives with product strategy and KPIs.

Requirements

  • MSc or PhD in Computer Science, Machine Learning, or a related field.
  • Strong ML engineering experience with proficiency in PyTorch.
  • Hands-on experience with Databricks.
  • Expert-level skills in Python and PySpark for large-scale data processing.
  • Familiarity with cloud platforms (AWS) and data warehousing (Snowflake).
  • Strong understanding of CI/CD workflows and best practices.

Nice to Have

  • Experience with MLOps practices.
  • Knowledge of distributed systems and neural network architectures.

What We Offer

  • Competitive salary and bonus structure.
  • Comprehensive health coverage.
  • Generous PTO and company holidays.
  • Flexible remote working options.

If you're passionate about building scalable ML systems and want to work in a dynamic, innovative environment, apply today to learn more about this Senior Machine Learning Engineer remote opportunity.

Why This Job8.5 of 10

This Senior Machine Learning Engineer role offers a competitive salary and the chance to work with cutting-edge AI technologies in a fully remote setting.

Salary Range
Required
0/1
Optional
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Bonus
0/1

About Harnham

Explore Harnham careers in 2026 and discover exciting job opportunities tailored for you. Whether you're looking for remote, hybrid, or office roles, our platform offers advanced filters, application tracking, and valuable company insights to help you find your ideal position. Stay updated with Harnham's latest openings and elevate your career with us today!

Industry
Tech
Location
Remote

Who Will Succeed Here

Proficient in Python and experienced with frameworks such as PyTorch and PySpark, demonstrating the ability to architect and train complex neural network models for optimization tasks.

Self-motivated and disciplined, thriving in a fully remote work environment, with excellent time management skills to balance multiple projects and deadlines across different time zones.

Possesses a strong analytical mindset and a deep understanding of data pipeline architectures, with hands-on experience in cloud services like AWS and data warehousing solutions like Snowflake.

Learning Resources

Deep Learning with PyTorch: A 60 Minute Blitzguide

Career Path

Senior Machine Learning Engineer(Now)Lead Machine Learning Engineer(1-2 years)Machine Learning Architect(3-5 years)

Market Overview

Market Size 2024
$45B
Annual Growth
22.5%
AI Adoption
75%
Investment in ML Technologies
+150%
Labour Demand for ML Engineers
+40%
Avg Salary for ML Engineers
$130K

Skills & Requirements

Required
PythonPyTorchPySpark
Growing in Demand
TensorFlowMLOpsNatural Language Processing (NLP)
Declining
RMatlab

Domain Trends

Increased Investment in AI Startups
Investment in AI startups reached $40 billion in 2023, with a projected increase of 150% in 2024, indicating a robust growth in demand for machine learning solutions.
Shift to Cloud-Based ML Solutions
Over 60% of organizations are now utilizing cloud platforms like AWS and Azure for machine learning projects, driving the need for cloud-savvy engineers.
Focus on Ethical AI
Approximately 70% of companies are prioritizing ethical AI practices, leading to a growing demand for skills in responsible AI design and implementation.

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