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
0/1
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 machine learning frameworks such as PyTorch, demonstrating the ability to architect and optimize neural network models for large datasets and complex problems.

Self-motivated and disciplined in a remote work environment, capable of independently managing projects and timelines while effectively collaborating with distributed teams using tools like Slack and GitHub.

Hands-on experience with cloud platforms, specifically AWS and Snowflake, showcasing a strong understanding of data engineering principles and the ability to implement scalable solutions in a cloud-native architecture.

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
$62.5B
Annual Growth
22.5%
AI Adoption
85%
Investment
+150%
Labour Demand
+30%
Avg Salary
$135K

Skills & Requirements

Required
PythonPyTorchPySpark
Growing in Demand
TensorFlowKubernetesNatural Language Processing (NLP)
Declining
RMapReduce

Domain Trends

Increased Demand for Cloud-based ML Solutions
With 70% of enterprises shifting to cloud-based machine learning solutions, skills in AWS and Databricks are becoming essential.
Rise of Automated Machine Learning (AutoML)
The AutoML market is projected to grow by 25% annually, pushing engineers to focus on automation tools rather than traditional model building.
Emphasis on Data Privacy and Ethics in AI
Over 60% of organizations are prioritizing ethical AI practices, leading to a demand for engineers who understand data governance and compliance.

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