Velir
SeniorAI/MLEngineer
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“Senior AI/ML Engineer at Velir. Skills: AI/ML, LLM, MLOps. Design AI/ML systems. Build AI/ML systems”
What They're Looking For.
Must Have
5+ years experience, Python proficiency, SQL proficiency
Nice to Have
PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, dbt Certified certification
What You'll Do.
Build LLM applications
Define evaluation strategies
Influence technical direction
How You'll Work.
Team & Collaboration
Cross-functional teams; Technical stakeholders
Communication Scope
Technical communication; Non-technical communication
Full Job Description
Velir is an established mid-sized agency with a top-tier portfolio of clients, ranging from the world’s largest non-profits to Fortune 500 brands. As of 2023, Velir acquired Brooklyn Data Company, a premier data and analytics consultancy focused on leadership, process improvement, implementation, and advanced analytics. At Velir, we believe people are our greatest asset. Our culture is built on a foundation of trust, collaboration, and continued improvement. We strive for excellence in everything we do, embracing challenges as opportunities for growth. Our success is driven by a shared passion for making a positive impact on our customers, our communities and each other. We are a remote first company that offers competitive pay and excellent benefits. Overview Senior AI/ML Engineers are senior individual contributors who design, build, and deploy production-grade AI/ML systems for both client-facing and internal products. They partner with leadership and cross-functional teams to translate business needs into scalable ML and LLM-based solutions. This role does not typically include direct reports but requires strong technical leadership, mentorship, and influence across teams. Responsibilities AI/ML System Design experience with PyTorch and HuggingFace Experience building LLM applications, including RAG, embeddings, and vector search Experience with cloud platforms (AWS or Azure; e.g., SageMaker, Bedrock, Azure ML) Strong understanding of ML fundamentals: data design, training, evaluation, and experimentation Familiarity with LLM alignment techniques (e.g., SFT, DPO, RL) Experience with MLOps practices: CI/CD, monitoring, retraining, and experiment tracking Proficiency working with complex, multi-source datasets and defining evaluation strategies Strong software engineering fundamentals (testing, modularity, code review) Experience mentoring engineers and influencing technical direction Strong communication skills with both technical and non-technical stakeholders T
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