Lead the end-to-end machine learning lifecycle, including data ingestion, model development, training, evaluation, deployment, monitoring, and iteration
Own and evolve ML Ops architecture, including CI/CD for models, feature pipelines, model versioning, monitoring, and retraining strategies
Serve as a player-coach, contributing directly to design reviews, code reviews, prototyping, and implementation for high-impact initiatives
Architect and deploy computer vision models (e.g., CNNs, transformers, multimodal models) and LLM-based systems (e.g., prompt pipelines, fine-tuning, RAG, evaluation frameworks)
Establish and track model performance, reliability, scalability, and ethical AI metrics, ensuring compliance with internal standards and regulatory expectations
Lead project planning, feasibility analysis, and technical scoping for new AI-driven functionality
Identify technical risks early and develop mitigation and contingency plans
Maintain and design software primarily in Python, with the ability to contribute to or review code in C/C++, Java, JavaScript, C#, and mobile frameworks as needed
Ensure strong testing discipline, including unit testing, integration testing, and test-driven development (TDD) practices
Apply and mentor on software design patterns, debugging strategies, and production troubleshooting best practices
Collaborate cross-functionally to align priorities, manage dependencies, and communicate progress, tradeoffs, and outcomes
Write and present technical and executive-level status updates to stakeholders
Oversee software and model releases and communicate release readiness and impact

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (Master’s preferred)
7+ years of professional experience in machine learning or related engineering roles
1–3+ years of people leadership experience, preferably managing ML or data-focused teams
Demonstrated, hands-on experience with computer vision frameworks (e.g., PyTorch, TensorFlow, OpenCV)
LLMs and modern NLP systems, including prompt engineering, fine-tuning, evaluation, and deployment
At least two machine learning frameworks
Strong proficiency in Python; experience with production-grade ML systems
Proven ability to define, estimate, and deliver complex technical projects on schedule
Experience designing task hierarchies, managing scope across features and epics, and balancing technical debt with delivery
Excellent communication skills with both technical and non-technical stakeholders
Demonstrated initiative in improving systems, processes, and codebases
Strong collaboration skills and a positive, team-first mindset.

Benefits

AvaSure sponsored Medical, Dental & Vision
Safe Harbor 401K with Employer Matching up to 4%
HSA Employer Contributions
Employer Paid Life, Short-term and Long-term Disability, and AD&D Insurance Plans
Flexible Time Off Plan & Paid Holidays
Parental Leave
Generous Tuition & Continuing Education Reimbursement available
Employee Referral Bonus

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningcomputer visionPythonC/C++JavaJavaScriptML OpsCI/CDtest-driven developmentsoftware design patterns

Soft Skills

leadershipcommunicationcollaborationproject planningrisk managementinitiativeteamworkmentoringproblem-solvingstakeholder management

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in EngineeringBachelor’s degree in Data ScienceMaster’s degree in related field