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Dynata

Senior Machine Learning Engineer

Posted 21 Days Ago
Remote
Hiring Remotely in U.S.A.
100K-150K Annually
Senior level
Remote
Hiring Remotely in U.S.A.
100K-150K Annually
Senior level
As a Senior Machine Learning Engineer, you will optimize business efficiency and respondent experience through advanced ML solutions, focusing on model lifecycle management, MLOps, and collaboration with engineering teams.
The summary above was generated by AI

We’re looking for a Senior Machine Learning Engineer to optimize survey respondent experience and business efficiency through advanced ML solutions. You’ll work on supervised learning, reinforcement learning (RL), and large language models (LLMs) to improve how we match respondents to surveys and ensure quality while maximizing business impact.

This role demands autonomy, deep technical expertise, and a strong ability to mentor others in MLOps best practices. You’ll collaborate with data engineers, software engineers, and product teams while helping design, develop, and scale our ML infrastructure on AWS.

What You’ll Do

  • Develop, deploy, and maintain ML models that optimize respondent experience and business efficiency.

  • Lead MLOps initiatives, including designing, developing, and scaling ML pipelines.

  • Work with real-time and batch inference systems to serve models effectively.

  • Own model lifecycle management, from experimentation to production.

  • Collaborate with engineers and product teams to integrate ML solutions seamlessly.

  • Mentor team members, providing guidance on best practices in ML development and MLOps.

  • Write and optimize SQL queries to extract insights and enhance model performance.

  • Drive technical discussions, ensuring we use the right tools and methodologies for scalability.

What You Need

  • Proven experience (senior level) in building, deploying, and scaling ML models in production.

  • Deep understanding of supervised learning, RL, HFRL, and LLMs.

  • Strong MLOps expertise – you’ll be the key person driving our ML infrastructure forward.

  • Experience with AWS services for ML development and deployment.

  • Proficiency in SQL, capable of writing complex queries as needed.

  • Ability to work autonomously and make key technical decisions.

  • Strong collaborator and team player – no egos, just results.

  • Experience mentoring others and teaching best practices in ML development & MLOps.

Why Join Us?

  • Ownership & Autonomy – You’ll have the freedom to shape our ML stack.

  • Cutting-Edge Tech – Work on the latest in RL, LLMs, and scalable MLOps.

  • Collaborative Culture – No bureaucracy, just a team working together to solve hard problems.

  • Impact-Driven – Your work will directly optimize how we engage with millions of respondents.

At Dynata, we are committed to fostering an inclusive, accessible environment, where all employees and customers feel valued, respected and supported. We are dedicated to building a workforce that reflects the diversity of our customers and communities in which we live and serve. Dynata welcomes and encourages applications from people with disabilities. We are committed to an inclusive work culture for all our employees. Accommodations by request can be made for all aspects of the selection process.

Dynata is also an affirmative action employer OE/Minority/Female/Veteran/Disabled/Sex/Sexual Orientation/Gender Identity or Expression/Race/Color/National Origin/Age/Religion/Genetic Information/Marital Status/Height/Weight or any other legally protected category defined by applicable federal state or local laws and ordinances, so as to further the principles of equal employment opportunity.

The base salary range for this position in is $100K-$150K/yr; however, base pay offered may vary depending on location, job-related knowledge, skills, and experience. A discretionary incentive program may be provided as part of the compensation package, in addition to a full range of medical and other benefits, dependent on full-time employment status.  

Top Skills

AWS
Large Language Models
Mlops
Reinforcement Learning
SQL
Supervised Learning

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