Prime Medicine
Prime Medicine, Inc., a biotechnology company, engages in delivering genetic therapies to address the spectrum of diseases by deploying gene editing technology in the United States.
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· 199 views · 26 applications · 18d
AI/ML Engineer
Full Remote · Worldwide · Product · 2 years of experience · Advanced/Fluent## Job Opening: AI/ML Engineer Location: Full Remote Job Type: Full-Time Salary Range: $3,000 – $6,000 USD / month Experience Level: Mid to Senior (3–5+ years) --- ### About the Role We're seeking a versatile and innovative AI/ML Engineer to join our...## Job Opening: AI/ML Engineer
Location: Full Remote
Job Type: Full-Time
Salary Range: $3,000 – $6,000 USD / month
Experience Level: Mid to Senior (3–5+ years)---
### About the Role
We're seeking a versatile and innovative AI/ML Engineer to join our growing team. This role sits at the intersection of data science, machine learning, NLP, and software engineering. You'll be designing and deploying production-grade machine learning systems, experimenting with cutting-edge LLMs, and solving real-world problems using unsupervised learning, graph-based models, and distributed systems.
You’ll collaborate cross-functionally with product managers, designers, and engineers to shape how we leverage AI across our platforms—from education to healthcare.
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### Responsibilities
- Design, prototype, train, and deploy LLMs and traditional ML models for:
- Semantic understanding, emotion detection, expressive summarization
- Text clustering, topic modeling, and classification
- Intent/sentiment extraction and entity resolution
- Recommendation systems and agentic RAG systems
- Develop clean, scalable ML pipelines and integrate them with existing systems using APIs and batch services
- Collaborate with cross-functional teams to understand user needs and translate them into AI-powered solutions
- Manage full ML lifecycle: from data wrangling (SQL, pipelines) to model deployment (cloud-based environments)
- Build knowledge graphs and explore Graph Neural Networks (GNNs) for structured reasoning
- Experiment with new ML approaches and keep up with advances in modern NLP and distributed inference
- Monitor, evaluate, and continuously improve model performance in production
- Document solutions and communicate results clearly to both technical and non-technical stakeholders---
### Requirements
- 3–7+ years of experience building and deploying ML systems (production experience a must)
- Strong hands-on skills in:
- Python and SQL
- NLP libraries (Spacy, NLTK, HuggingFace, etc.)
- Deep learning frameworks (PyTorch, TensorFlow, JAX)
- Working knowledge of:
- Modern NLP and LLM finetuning
- Unsupervised techniques like clustering and topic modeling
- Semantic similarity, summarization, classification, sentiment/emotion detection
- Distributed training/inference and cloud infrastructure (AWS, Azure, or GCP)
- Experience with:
- Microservices and API integrations
- Docker, Kubernetes, and containerized ML deployments
- MLOps practices: CI/CD for ML, model monitoring, and pipeline automation
- Familiarity with domain-driven design and scalable, decoupled architectures
- Strong communication and storytelling ability to tie technical work to product and business outcomes---
### Bonus Skills
- Experience with graph-based ML (Knowledge Graphs, GNNs, DGL)
- Exposure to networked, multi-rank GPU environments
- Background in data engineering or DevOps
- Data visualization for ML explainability and diagnostics
- Passion for education, healthcare, or social impact applications---
### Who You Are
- You connect the dots: You see the big picture and align your work with user and business impact.
- You make high-leverage bets: You act strategically with speed and resourcefulness.
- You simplify and ship: You focus on essentials, iterate fast, and get things into production.
- You think from first principles: You question assumptions and explore new paths.
- You’re naturally curious and proactive about learning and experimenting.---
### What We Offer
- Competitive compensation and performance-based bonuses
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- Flexible hybrid/remote work schedule
- Health, dental, and vision insurance
- A collaborative, mission-driven team environment
- Opportunities for professional growth, mentorship, and innovation
- The chance to work with cutting-edge ML systems in a meaningful space