Velir
Senior AI/ML Engineer
Remote AI ML Engineering role with clear candidate location fit.
PostedJul 4, 2026
Eligible countries8 accepted countries
Seniority signalSenior
Work settingRemote
Accepted candidate locations
Role overview
Senior AI/ML Engineer
Requirements and responsibilities
Readable role content extracted into sections for faster review.
AI/ML System Design & Leadership
- Lead the design and implementation of scalable ML systems, including supervised, unsupervised, and LLM-based solutions
- Translate research and prototypes into production-ready systems
- Partner with stakeholders to identify high-impact AI/ML opportunities and define optimal technical approaches
- Provide technical mentorship and contribute to team upskilling
LLM & Production AI Systems
- Build and operate LLM pipelines, including prompt design, fine-tuning, and evaluation
- Develop RAG-based systems using embeddings, vector stores, and retrieval strategies
- Design evaluation frameworks, feedback loops, and datasets to continuously improve model performance
- Create reusable tooling to accelerate experimentation, deployment, and monitoring
MLOps & Deployment
- Own end-to-end ML lifecycle: data pipelines, training, deployment, monitoring, and iteration
- Establish best practices for reproducibility, observability, CI/CD, and model versioning
- Partner with platform/DevOps teams to ensure reliability and scalability
- Promote responsible AI practices, including governance, fairness, and transparency
Cross-Functional Collaboration
- Lead cross-functional initiatives across data engineering, analytics, and AI/ML
- Translate complex ML concepts into clear recommendations for technical and non-technical audiences
- Collaborate with clients and internal teams to plan and deliver AI/ML solutions
- Contribute documentation, frameworks, and shared best practices
Project Execution
- Scope and lead complex AI/ML initiatives aligned to business outcomes
- Align stakeholders and drive execution across teams
- Establish clear success metrics and ensure delivery of high-impact solutions
Skills & Qualifications
- 5–7 years of experience in ML engineering, AI engineering, or related fields, with production deployment experience
- Strong programming skills in Python and SQL; 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
Tech Stack
- Languages: Python, SQL
- Frameworks: PyTorch, HuggingFace
- Platforms: AWS, Azure, Snowflake, Databricks
Physical Requirements
- Frequent sitting at a desk performing work on a computer
- Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions
Core Company Values
- Take the Long View - Ensure the company is built to last
- Be Courageous - Make the right decisions even when they aren't the easiest decisions
- Be Genuine - Bring honesty and authenticity to all that you do
- Work with Focus + Passion - Display purpose and pride in your work and never stop learning
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