Staff Engineer/AI-ML Engineer
India GCC-Puppalaguda Village Full-time Senior Machine Learning Engineering
At a glance
Senior Machine Learning Engineering role at The Hartford. India GCC-Puppalaguda Village · full-time.
Pay not stated Machine Learning Engineering salary
RoleMachine Learning Engineering
SenioritySenior
LocationIndia GCC-Puppalaguda Village
EmploymentFull-time
PostedJun 5, 2026 · 4mo ago
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Build and maintain models as services, taking them from design through deployment and ongoing upkeep
- Test and put generative AI and machine-learning approaches into use, assessing new data and analytical methods
- Deliver model deployments on AWS and GCP, and encourage MLOps practices among data science colleagues
- Coordinate with data, business, cloud and architecture partners to align work and meet deployment milestones
- Guide junior engineers, review deliverables with partners and leaders, and present technical ideas to technical audiences
What you bring
- You have development experience across both AWS and GCP tools
- You bring strong Python, Java or C# object-oriented development skills
- You have built cloud-hosted web services and CI/CD pipelines using Jenkins or a comparable tool
- You can design infrastructure as code and use GitHub at an expert level, including GitHub Actions
- You understand the model lifecycle, from early development through production monitoring
Who this fits
This senior engineering role suits someone who can combine cloud development with model delivery and collaborate across technical and business teams. You’ll also mentor junior engineers and contribute as a technical leader.
From the employer
IND Staff Engineer - GCC094
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.
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.
Minimum Requirements
- 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
- ML engineering, data manipulation and application development
- Python development experience
- Working with IAC, developing CICD pipelines
- Experience in the insurance or broader financial services industry
- SQL development experience
- Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM’s into automated processes