Jobs via Dice · 1 hour ago
Staff Machine Learning Engineer
United States
Full-time
Remote
Senior Level, Lead/Staff
$150K/yr - $195K/yr
7+ years expDice Talent Solutions is seeking a Staff Machine Learning Engineer to help establish and lead their Machine Learning Engineering function. This role will be instrumental in shaping the future of the client’s ML and LLM capabilities while driving innovation across traditional ML pipelines and AI applications.
Computer Software
No H1B
Hiring Manager
Michael Lebenkoff
Responsibilities
Architect and lead the development of scalable ML infrastructure for training, inference, and model lifecycle management
Design and implement systems for ML experiment tracking, model registry, and feature store integration
Establish frameworks for bias and fairness assessment across ML models and ensure compliance with internal and external standards
Develop infrastructure and tooling for real-time and batch model inference
Collaborate with data scientists, engineers, and product teams to translate business needs into new ML solutions
Support Software Engineering teams in their development of LLM products by establishing and managing shared LLM infrastructure for governance, observability, and cost management
Mentor and guide a team of ML engineers, fostering a culture of innovation, transparency, and technical excellence
Qualification
Required
7+ years of experience in Machine Learning Engineering or Applied ML, with 2+ years of leadership experience
Expertise in ML infrastructure, model lifecycle management, and experiment tracking tools (e.g., MLflow, Weights & Biases)
Hands-on experience with LLM development, including prompt tuning, RAG architectures, and vector databases (e.g., Qdrant, Pinecone)
Strong understanding of bias and fairness metrics, and experience implementing auditing frameworks
Proficiency in big data tools and cloud platforms (e.g., AWS, GCP, Azure, Snowflake, Spark)
Strong software engineering skills in Python and experience with containerization and orchestration (e.g., Docker, Kubernetes)
Experience managing ML costs and optimizing cloud resource usage
Excellent communication and collaboration skills, with a track record of cross-functional leadership
Passion for building scalable, transparent, and impactful ML systems
Preferred
Experience in a startup environment
Bachelor's Degree in Computer Science or similar degree
Experience with boosted models like XGBoost
Experience with LLM Voice agents
Familiarity with Healthcare data
Company
Jobs via Dice
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0-1 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase