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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Machine Learning Engineer - **Company:** The Hartford - **Location:** Hartford, CT, United States - **Experience:** Expert - **Salary:** $117,200.0 - $175,800.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Architectural Patterns, CA Workload Automation Ae, Big Data, BigQuery, C Sharp (Programming Language), Cloud Engineering, Continuous Integration, Data Structures, Relational Databases, Database Development, DevOps, Github, Apache Hadoop, Apache Hive, Python (Programming Language), Machine Learning, Object-Oriented Software Development, Tensorflow, Web Application Security, Software Engineering, Web Services, Enterprise Data Management, Data Processing, Large Language Models, Snowflake, Apache Spark, Generative AI, Cloudformation, Scikit Learn, Kubernetes, Machine Learning Operations, Streamlit Framework, Terraform, Data Pipelines, Api Management, Docker, Jenkins - **Published:** August 7, 2026 - **Apply:** https://www.juju.com/job/00000000glx3lp ## About the Role + Must be authorized to work in the U.S. now and in the future. + Master's degree in related field or 5+ years of equivalent experience in a research or DevOps function. + Development experience using both the AWS and GCP suite of tools. + Familiarity with SageMaker, Streamlit, web security, credentials and API management tools + Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns. + Experience building and deploying webservices in a cloud environment. + Experience building CICD pipeline using Jenkins or equivalent + Experience with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or similar + Expert-level Github experience, including Github Actions + Strong object oriented development experience using Python, Java, C# + Familiarity with big data technologies (i.e. Hadoop, Spark, Hive, etc.) and RDBMS platforms such as Redshift, Snowflake or BigQuery + Experience in end to end model development lifecycle, from ideation through post production monitoring. + Experience with workflow automation platforms (Apache Airflow, Autosys, similar) + Experience with Solution Design and Architecture of data pipelines + Basic understanding of Data Science model development life cycle Preferred Skills + Fundamentally strong with Data Structures and algorithms. + Experience working with Docker, Kubernetes and EC2 environment. + Experience building ML and data pipeline and orchestration services + Basic understanding of ML frameworks i.e. Tensorflow, Anacoda, Scikit Learn, + Experience working in an Agile framework. Qualifications + 4+ years of ML engineering, data manipulation and application development + 4+ years Python development experience + 4+ years working with IAC, developing CICD pipelines + 1+ years of experience in the insurance or broader financial services industry + 1+ years SQL development experience + Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM's into automated processes This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday). Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position. ## Description As a **Senior Machine Learning Engineer** , you will play a critical role in designing, building, and operationalizing production-grade AI solutions-partnering closely with product, engineering, and operations leaders to deliver measurable impact. Our core values + We build AI solutions, not models. We are thoughtful in supporting the end-to-end business problem, with an eye to systems design. + We are trusted and transparent. We collaborate tightly with our partners and are mindful of their capacity to absorb change. + We provide assets that are safe to buy. Our products are delivered with a full monitoring solution to ensure our products continue to deliver as expected. + We will earn the right to influence. With humble confidence, we listen carefully to learn from our customers and become partners in problem solving. + We are practical and evolutional. We first deliver a minimally viable product and over time expand its sophistication based on feedback. Responsibilities + Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies. + Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage. + Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations. + Accountable for design, development and maintenance of Models as Service + Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences. + Collaborate with partners Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams + Delivery of critical milestones for model deployment in the AWS and GCP clouds. + Adopt and promote MLOps best practices to the Data Science community. ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Got AI ideas but no money? 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