Senior AI/ML Engineer: Data Science & MLOps Leader

Infosys Limited; Austin, Northern (TX, KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Disability Insurance

401(k) plan

Health & Dependent Care Accounts

Job summary

Infosys DNA invites applications for a Data Science Consultant 2 to drive scalable analytics and AI-driven solutions across business units in the U.S. You will lead technically, mentor engineers, and deliver production-ready models leveraging MLflow, Kubeflow, SageMaker, and cloud platforms.

You will collaborate with data scientists and engineers to operationalize models, implement governance, and contribute to IP assets, with opportunities for thought leadership and ongoing training.

Qualifications

• Experience in AI/ML, data engineering, data science, or cloud engineering.
• Leadership or supervisory experience leading technical teams.
• Strong proficiency in Python and ML development frameworks.
• Hands-on experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Azure ML.
• Experience with cloud platforms (Azure, AWS, or GCP).
• Strong understanding of data engineering concepts, ETL/ELT pipelines, and large-scale data processing.
• Experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Excellent problem-solving, communication, and stakeholder management skills.
• Design, develop, and deploy scalable machine learning and AI solutions for business-critical applications.
• Lead a team of AI/ML engineers and provide technical guidance, mentoring, and code reviews.
• Build and maintain MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
• Collaborate with Data Scientists and Data Engineers to operationalize ML models into production environments

Responsibilities

• Develop data preparation tasks, while identifying patterns or anomalies.
• Ensure data readiness for advanced modeling.
• Develop models for complex use cases (e.g., forecasting models, LLM-based solutions).
• Refine algorithms to meet business needs and deploy into production-ready solutions.
• Conduct testing and optimize algorithms for performance, reliability, and scalability.
• Design and develop predictive models and data-driven analyses to address business challenges.
• Build, evaluate, and deploy models, standardize code, and contribute to knowledge management.
• Leverage SAS and R/Python to create reusable customizations for ML algorithms, including LLMs.
• Define analytics problems; execute visualization, analysis, and predictive modeling under guidance.
• Proactively maintain models and implement improvements for accuracy and reliability.
• Apply governance controls to mitigate risks and ensure compliance.
• Analyze performance trends, recommend improvements, document discrepancies for escalation.
• Maintain documentation standards, participate in knowledge transfer sessions.
• Discuss with stakeholders to refine requirements and guide model implementation.
• Apply the predefined quality measurement framework at task level.
• Deploy analytics tools or multi-system integration; validate deployment success.
• Develop scripts/templates for repeated deployments.
• Contribute to analytic solutions, IP asset creation, and training initiatives.
• Contribute to thought leadership and proofs of concepts.
• Deliver analytics training and content creation.
• Provide input for segment and unit-level business plans.

Skills

Python

ML Frameworks

MLOps

Cloud Platforms

Data Engineering

Docker/Kubernetes

Leadership

Stakeholder Mgmt

Education

Bachelor's degree

Tools

MLflow

Kubeflow

SageMaker

Azure ML

Job description

Infosys DNA invites applications for a Data Science Consultant 2 to drive scalable analytics and AI-driven solutions across business units in the U.S. You will lead technically, mentor engineers, and deliver production-ready models leveraging MLflow, Kubeflow, SageMaker, and cloud platforms.

You will collaborate with data scientists and engineers to operationalize models, implement governance, and contribute to IP assets, with opportunities for thought leadership and ongoing training.