Principal AI/ML Engineer

About the role

Pragmatike is hiring on behalf of a fast-growing AI startup recognized as a Top 10 GenAI company by GTM Capital, founded by MIT CSAIL researchers. We are looking for a Senior AI/ML Engineer to join a high-performing AI engineering team building and deploying real-world AI systems used by Fortune 500 customers.

Responsibilities

• Design, build, train, and optimize machine learning and deep learning models for production use
• Lead the deployment of ML models into scalable, reliable production systems
• Architect training, inference, and evaluation pipelines for structured and unstructured data
• Own model performance, reliability, scalability, and lifecycle management
• Drive experimentation, model iteration, and performance benchmarking
• Implement and maintain high-quality ML codebases primarily in Python
• Monitor, debug, and improve live production models
• Collaborate with platform, backend, and infrastructure teams on system integration
• Contribute to technical direction, architecture decisions, and AI roadmap planning
• Mentor junior engineers and support team-level technical excellence

Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Mathematics, or a related field
• 7+ years of professional experience in AI/ML, data science, or applied machine learning roles
• Proven experience deploying ML systems into production environments
• Strong understanding of ML fundamentals, evaluation methodologies, and model lifecycle management
• Deep hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
• Strong proficiency in Python
• Experience designing scalable ML systems and pipelines
• Able to operate independently and take technical ownership of complex systems
• Strong problem-solving, architecture, and system-design skills

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Mathematics, or a related field
• 7+ years of professional experience in AI/ML, data science, or applied machine learning roles
• Proven experience deploying ML systems into production environments
• Strong understanding of ML fundamentals, evaluation methodologies, and model lifecycle management
• Deep hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
• Strong proficiency in Python
• Experience designing scalable ML systems and pipelines
• Able to operate independently and take technical ownership of complex systems
• Strong problem-solving, architecture, and system-design skills

Skills

• Experience with deep learning, LLMs, GenAI, or modern AI architectures
• Experience building AI systems used by enterprise or large-scale customers
• Strong experience with cloud platforms (AWS, GCP, Azure)
• MLOps experience (CI/CD for ML, model deployment, monitoring, observability)
• Research background, publications, or applied AI innovation projects
• Experience leading AI initiatives or mentoring ML engineers

Benefits

• Competitive salary & equity options
• Sign-on bonus
• Health, Dental, and Vision
• 401(k)