We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.   

The Hartford’s Personal Lines Data Analytics team seeks energetic and passionate Senior Machine Learning Engineer to build Machine Learning Operations (MLOps) & Generative AI (GenAI) services for data science teams. Our Data science team has developed industry-leading capabilities, driving streamlined processes and smarter decision making. As a Senior Machine Learning Engineer within the MLOps team, you will play a significant role in delivering modern and sustainable data science products generating meaningful outcomes for the enterprise.

This role can have a Hybrid or Remote work arrangement. Candidates who live near one of our locations will have the expectation of working in an office 3 days a week (Tuesday through Thursday). Candidates who do not live near an office should maintain their current work arrangement with the expectation of coming into the office as business needs arise.

We are looking for talent who embraces our core values:
 

• We build AI/ML 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 framework, tools, and technologies to enable AI/ML decision making at scale.
• Participate in identifying and assessing opportunities i.e., value of new data sources and analytical techniques to ensure ongoing competitive advantage.
• Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations.
• Accountable for the ownership of design, development, and maintenance of MLOps and GenAI platform and services.
• Work with junior engineers and peers to provide mentorship and thought leadership.
• 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 cloud.
• Develop, adopt, and promote MLOps best practices to the Data Science community.
• Present new development and innovation in the various data and analytics forums.

Minimum Requirements

• 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 function.
• Fundamentally strong with Data Structures and algorithms.
• Experience building and deploying WebServices using RESTful API in Cloud environment. 
• Experience building CICD pipeline using Jenkins or equivalent.
• Strong application development experience using Python or Java in AWS or other public cloud environment.
• Familiarity with big data technologies (i.e., Hadoop, Spark, Hive, etc.) and RDBMS.
• Good understanding of Generative AI technologies, frameworks, key LLMs, and architecture patterns
• Experience in end-to-end model development lifecycle, from ideation through post-production monitoring.
• Experience with Solution Design and Architecture of data and ML pipelines as well as integrating with Enterprise systems.
• Good understanding of Data Science model development life cycle such as Model training and experimentation, model deployment, model log management, model monitoring and feedback loop.
• Good understanding of various model development algorithms and types of ML usecases e.g., regression, classification, etc.
• Good understanding and experience building orchestration framework for real-time and batch model services. 

Preferred Skills:

• Development experience for WebService API with AWS suite of Tools.
• Familiarity with Sage Maker, Python Flask, or Spring Boot.
• Experience working with VMs, Docker, Kubernetes and EC2 environment.
• Basic understanding of ML frameworks i.e., Tensorflow, Anacoda, Scikit Learn, H20,
• Tools and techniques to auto scale applications in Cloud environment
• Familiarity with credentials management using vault services, protecting API using tokens.
• Familiarity with Building and deploying services using IaaC templates e.g Cloud Formation or Terraform
• Experience with Agile framework and scrum/Kanban based project management.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

Equal Opportunity Employer/Females/Minorities/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

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