bolt is looking for a Lead AI and Machine Learning Engineer to join our growing AI & Data Analytics team. This is a unique opportunity to work on real-world GenAI and traditional ML problems across a complex, multi-tenant SaaS platform. You’ll play a critical technical role in designing, developing, and deploying AI-powered capabilities—helping shape the future of insurance. 

This is a hands-on technical role focused on building, deploying, and optimizing AI/ML solutions that directly impact our customers' success in the insurance industry. You’ll also be instrumental in laying the foundation for a growing team—providing technical leadership and mentorship, but not managerial duties at this stage.

You’ll work on:

• Building and deploying AI/ML and GenAI (LLMs, RAG) solutions
• Integrating ML into production at scale (microservices-based architecture)
• Rapid prototyping and MVP development
• Research and evaluation of new AI trends, tools, and techniques

AI/ML Model Development

• Design, develop, and deploy machine learning models for predictive analytics, risk assessment, and business optimization
• Build and implement GenAI and LLM solutions to address specific insurance industry challenges
• Develop NLP models and applications including chatbots, document processing, and text classification
• Create RAG-based applications using foundation models

Research & Innovation

• Drive research initiatives in machine learning, deep learning, and statistical modeling
• Stay current with AI/ML advances and evaluate new technologies for potential adoption
• Design and execute experiments to validate model performance and business impact
• Conduct rigorous statistical analysis, hypothesis testing, and causal inference

Technical Leadership

• Own end-to-end ML project delivery: from data gathering and feature engineering to model deployment and monitoring
• Establish MLOps practices and CI/CD pipelines for model deployment
• Build scalable, cloud-native ML infrastructure and APIs
• Create technical documentation and best practices for future team members

Collaboration & Impact

• Work closely with Engineering, Product, and Business teams to translate requirements into technical solutions
• Present findings and model results to stakeholders across the organization
• Ensure models deliver measurable business value and actionable insights
• Mentor and guide junior team members as the team grows

We expect you to be able to demonstrate the following key competencies: 

• Impactful
  • Has a clear understanding of team’s objectives and aligns efforts to these goals
  • Empowered to be quick to act and take steps to address issues
• Curious 
  • Engages in learning activities and is interested in understanding different ways of doing things including the key activities performed by others in team
  • Keeps up to date on relevant frameworks, applications, software, and/or tools
• Collaborative
  • Builds diverse networks and cooperative key working relationships to work in partnership with others
  • Co-operates with team members to resolve problems and achieve goals
• Creative 
  • Identifies beneficial new approaches and ways of looking at problems, introduces them within team
  • Experiments with new trends and innovations and is an early adopter where they can benefit team
• Literacy – Digital, Tech & Data
  • Proficient and competent in navigating and using digital, data and technology tools and software applications relevant to role including performing basic trouble shooting strategies 

Education & Experience

• Master's or PhD in Computer Science, Statistics, Mathematics, Engineering, or related field
• 10+ years of hands-on experience in data science, machine learning, and AI modeling
• Proven track record of deploying ML models in production environments
• Technical Skills

Programming & Data

• Expert proficiency in Python and SQL
• Strong understanding of object-oriented programming principles
• Experience with complex SQL queries and stored procedures
• Proficiency with big data tools (Hadoop, Hive, Spark)

Machine Learning

• Deep expertise in statistical modeling, including deep learning and reinforcement learning
• Hands-on experience with ML frameworks (TensorFlow, PyTorch, LangChain)
• Strong background in statistics, predictive modeling, and anomaly detection
• Experience with experimental design and A/B testing

GenAI & NLP

• Hands-on experience with foundation models and LLM applications
• Experience building RAG-based models (AWS Bedrock, Databricks preferred)
• Proven experience with NLP models and applications
• Knowledge of prompt engineering and fine-tuning techniques

Cloud & Infrastructure

• Experience with cloud platforms (AWS strongly preferred, Azure, GCP)
• Hands-on experience with MLOps tools (AWS SageMaker, MLflow, Kubeflow)
• Knowledge of containerization (Docker, Kubernetes)
• Experience with CI/CD pipelines and Infrastructure as Code (Terraform, CloudFormation)
• Proficiency with REST APIs, microservices architecture
• Linux environment experience

Tools & Platforms

• Git version control and collaborative development workflows
• API development and testing tools (Postman)
• Familiarity with data visualization and analytics tools

Soft Skills

• Excellent communication skills with ability to explain complex technical concepts to non-technical stakeholders
• Strong problem-solving mindset with focus on business impact
• Self-motivated with ability to work independently and take ownership
• Collaborative approach with cross-functional teams

Nice to Have

• Experience in the insurance or financial services industry
• Knowledge of regulatory compliance in AI/ML (model explainability, bias detection)
• Experience with real-time ML inference systems
• Background in causal inference and econometrics
• Open source contributions to ML/AI projects

https://www.boltinc.com/

At bolt, we are diverse and inclusive. We value each person's unique skills, background, and identity. We never discriminate on cultural background, religion, sex, gender, gender identity or expression, sexual orientation, age, disability, veteran status, genetic information, marital or family status or any legally protected status. Everyone belongs. And because everyone’s different, we’re also flexible in the ways we work, so each person can bring their best efforts every day.