About Minset:
---------------
Minset.ai is a VC-backed, early-stage deep tech AI startup building advanced AI systems to solve some of the hardest problems in U.S. healthcare Revenue Cycle Management (RCM).
We focus on:
- Denials management
- Autonomous medical coding
- Patient payments
Our work sits at the intersection of large-scale ML, GenAI, and real-world production systems in a highly regulated domain.
---------------
The Role:
We’re looking for a Senior Machine Learning Engineer to design, train, and deploy advanced ML and AI models across structured and unstructured healthcare data.
This is a hands-on role for someone who enjoys building and training models end-to-end; from data pipelines and training loops through evaluation and production deployment.
---------------
What You’ll Work On:
- Training advanced ML models on structured data
- NLP-first systems operating on clinical and financial unstructured data
- Computer vision models for document understanding
- Pretraining and post-training of models, including reinforcement learning.
- Agentic AI systems with reasoning and tool use
- Training at scale and large experimentation workflows
- End-to-end deployment of models into production healthcare systems
---------------
Desired Experience & Skills:
Experience
- 5+ years of hands-on experience in machine learning or applied AI
- Demonstrated experience training models end-to-end (not just consuming APIs)
Core Technical Skills
- Expert-level Python
- Strong experience with PyTorch
- Model optimization experience with libraries such as Unsloth
- Hands-on experience with distributed training frameworks such as DeepSpeed and Accelerate
- Strong background in NLP; experience with computer vision is a plus
- Experience working with large, text-heavy, messy datasets
- Solid understanding of optimization, loss & reward functions, training stability, and evaluation
LLM & GenAI Expertise
- Experience with post-training techniques (RL, SFT)
- Experience with model pretraining
- Ability to reason about training failure modes and evaluation trade-offs
- Experience building agentic AI systems (reasoning + tool use)
Data, MLOps & Cloud
- Experience building data pipelines; strong SQL skills
- Knowledge of MLOps, model versioning, and production deployment strategies
- Experience with orchestration tools
- Experience with Azure (preferred); GCP is a plus
---------------
What This Role Is Not:
This role is not a fit if your background is primarily:
- Prompt engineering without model training
- API-only usage of foundation models
- Limited exposure to training loops, optimization, or evaluation
- No experience deploying trained models into production
We’re looking for engineers who like to train, debug, and ship models.
---------------
Soft Skills:
- Excellent problem-solving skills and comfort working independently
- Strong communication skills with the ability to explain technical concepts to non-technical stakeholders
- Collaborative mindset and strong sense of ownership
---------------
Other Requirements:
- Physical residency in the U.S.
- U.S. permanent resident (Green Card holder) or U.S. citizen
---------------
Nice to Have:
- Contributions to open-source AI/ML projects
- Published research or technical writing in AI / ML
- Experience in healthcare / RCM
---------------
Benefits:
- Competitive salary
- Equity (depending on experience / performance)
- 401(k)
- Fully remote work with home office budget
- Health, dental, vision, and life insurance
- Uncapped PTO and sick days
Job Type: Full-time
Pay: $180,000.00 - $225,000.00 per year
Benefits:
- 401(k)
- Dental insurance
- Health insurance
- Health savings account
- Life insurance
- Paid time off
- Vision insurance
Application Question(s):
- Have you ever worked in an AI startup?
- Do you have any experience working in the healthcare space?
Education:
Experience:
- Machine learning: 5 years (Preferred)
Location:
Work Location: Remote
