Sr. ML Engineer

About us: bolt is the leading insurance exchange for the P&C insurance industry, uniting distributors, and providers on a single platform to transform the way insurance is bought and sold. The result is the world’s biggest exchange, working with two-thirds of America’s leading carriers and connecting more people with ways to protect the things they value. Profile Description: bolt is looking for Senior Machine Learning Engineer to join our growing analytics team on a full-time basis as part of the BOLT AI & Analytics group. Our product is a complex, multi-tenant, web-based SaaS platform, built on a micro services architecture. Analytics Team is responsible for delivering our customers with actionable insights, embedded on the SaaS platform. You will be a key player in our analytics team and take part in designing and delivering analytics solutions to new and existing customers. You will help integrate new technologies, capabilities, and methodologies. You will assist and mentor others to improve existing systems. You will take ownership of the analytics platform and help optimize the deliverables. You would be working with niche technologies to build the next-gen big data solutions. In addition, you will have opportunities to explore into the world of cloud computing, machine learning, artificial intelligence, self-service analytics, data services and many more Responsibilities: Developing and maintaining Machine Learning (ML) models used in our computer vision based diagnostic tool End-to-End Machine Learning Application delivery which includes Planning, Design, Development, Testing, and Delivery of Application(s) Developing open-source, cloud enabled, microservice based, scalable platforms that provide amazing consumer experience, whilst building cutting-edge technology that provides device protection with a unique value proposition Implementing requirements of the API layer like security, custom analytics, throttling, caching, logging, request, and response modifications etc. using the API management platform Implementing API monitoring and system support for production application services client facing environments Ensuring timely development of POC’s and prototypes prioritizing quick time to market with MVP features Applying Agile techniques to deliver key features quickly to ensure stories are delivered in incremental manner e.g., breaking down the stories in the right sizes, scheduling them, encourage sustainable workloads etc. Continuously research new technical capability and solutions for adoption Requirements: Master’s Degree or PhD in the fields of Computer Science, Statistics, or an equivalent with a minimum of 5 years of experience in data science and ML Ops Engineering Should have worked with at least one GenAI project Familiarity with Gen AI foundation models and Amazon Bedrock Should have expertise in Deep Learning & Reinforcement Learning techniques Should have experience in building statistical models using the above-mentioned techniques Should possess ability to build & deploy the models and interpret the results to business users Should have experience working with NLP models and building related applications such as chatbot, text-classifications, etc Should have experience working with big data tools – Hadoop, Hive, Spark. Proficiency in Python, good understanding of OOPs is a must. Worked with at least one mainstream machine learning framework such as Tensor Flow, py Torch, Lang chain Experience working with Cloud platforms (Azure, AWS, GCP) Should have ability to write complex SQL & stored procedures Should have experience in working with API’s - deploying models, extracting data. Should have good communication skills and ability to interact with customers Good grasp of Microservices based Architecture Previous hands-on experience in training and developing ML models is preferred Exposure to computer-vision based technologies and MLOps solutions from AWS/GCP is a major plus (AWS SageMaker, AWS Lambda, GCP Vertex etc.). AWS is preferred. Experience building applications using services provided by AWS such as S3, SQS, SNS and Kinesis Familiar with CI/CD tooling. CircleCI is preferred. Exposure to Infrastructure as code (IaC) tooling such as Terraform or CloudFormation is an advantage Knowledge in web services especially in REST API and tools such as Postman Working experience in a Linux based environment Knowledge in source code repository and branching models in Git and usage of tools such as GitHub, GitLab, BitBucket etc.