Senior Machine Learning Engineer

Harnham; San Francisco (CA); Remote; USD 180,000 - 200,000; Full time

Job summary

An established industry player in the AI sector is looking for a Senior Machine Learning Engineer to join their innovative team. In this role, you will design and deploy advanced machine learning models, including large language models, to tackle real-world business challenges. You will collaborate closely with product and engineering teams to ensure seamless integration and high performance of ML solutions. This position offers the opportunity to work with cutting-edge technologies and contribute to impactful projects in the advertising space. If you are passionate about machine learning and eager to drive innovation, this role is perfect for you.

Benefits

Bonus

Qualifications

• MSc or PhD in a STEM subject with commercial ML experience.
• Proven knowledge in machine learning and clustering techniques.

Responsibilities

• Design and deploy ML models to solve real-world challenges.
• Collaborate with teams to ensure ML solutions meet business goals.

Skills

Machine Learning

Data Science

Problem-solving

Communication Skills

Education

MSc in STEM

PhD in STEM

Tools

TensorFlow

Kubernetes

MLFlow

Kafka

Airflow

AWS

Spark

Job description

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This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$180,000.00/yr - $200,000.00/yr

Senior Machine Learning Engineer

Remote

Up to $200,000 + Bonus

Company:

A leading AI platform in the advertising space is seeking a Senior Machine Learning Engineer to help drive the development of its LLM and foundational model product suite. This role involves building and deploying advanced ML models to solve real-world business challenges with close collaboration across product and engineering teams.

Role:

• Design, build, and deploy machine learning models, including large language models (LLMs) and foundational models, to address real-world challenges.
• Develop and refine components within ML pipelines, focusing on LLM integration, robust monitoring, and seamless product implementation.
• Collaborate with product teams to ensure ML solutions align with business objectives and deliver meaningful user value.
• Work alongside engineering teams to embed models into production systems, optimizing for scalability, performance, and reliability.
• Apply deep technical knowledge to maintain high pipeline availability and ensure low-latency performance.
• Conduct experiments to explore new methodologies and continuously track model effectiveness in production environments.
• Utilize platforms such as AWS, Databricks, and Snowflake for resource management, model deployment, and artifact maintenance.
• Stay current with cutting-edge developments in ML, LLMs, and foundational models to drive innovation and solution enhancement.

Requirements:

• You need to have a MSc or PhD level in Stem subject.
• You must have proven knowledge in the implementation of Machine Learning and clustering techniques with commercial experience as a Data Scientist.
• DevOps experience in CI/CD.
• Experience using Tensorflow, Kubernetes, MLFlow, Kafka, and Airflow.
• Experience using Python is a must (tools like AWS and Spark are beneficial)
• Excellent communication skills and team and colleague engagement.
• A keen interest in problem-solving and using scalable machine learning to solve the biggest data-related problems.

Salary and Benefits

• Bonus

How to Apply

Please register your interest by sending your CV via the Apply link on this page.

Desired Skills and Experience

Machine learning engineering, MLOps

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Analyst

Industries

Software Development, Marketing Services, and Advertising Services