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IL
Infosys Limited
ML Engineer Analytics
Career Insights for Machine Learning Engineer
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Based on Texas data
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What they do
A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
$124,597 / year median in Texas
Job Description
Overview The Infosys Data and Analytics (DNA) unit is at the forefront of transforming data into actionable insights, driving business growth and operational efficiency. We specialize in leveraging advanced AI and analytics to create innovative solutions that address complex business challenges. Our team is dedicated to pioneering the future of data-driven decision-making, enabling organizations to unlock new opportunities and achieve sustainable success. Join us to be part of a dynamic team that is revolutionizing the way businesses harness the power of data and AI. At Infosys DNA, you'll have the opportunity to work with cutting-edge technologies, collaborate with industry experts, and contribute to transformative projects that shape the future of business. We are committed to fostering a culture of continuous learning and growth, ensuring that our team members thrive in a dynamic and supportive environment. If you're passionate about AI and eager to make a significant impact, the Infosys DNA unit is the perfect place for you to grow and excel. In the assigned Job Role of Data Science Consultant 2, your Area Of Responsibility will be as below:
- 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), while refining algorithms to meet business needs, and ensure smooth deployment into scalable, production-ready solutions.
- Conduct testing and optimize algorithms for performance, reliability, and scalability, while providing guidance to team members in best practices.
- 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 tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions.
- Define analytics problems for projects; 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, and document discrepancies for escalation.
- Maintain comprehensive documentation standards, while participating in knowledge transfer sessions.
- Participate in discussions with stakeholders to refine requirements, provide insights, and guide implementation of models.
- Apply the predefined quality measurement framework at an individual task level in the project.
- Deploy complex analytics tools or multi-system integration, while validating deployment success.
- Participate in developing scripts or templates for repeated deployments tasks.
- Contribute to analytic solutions, IP asset creation, and training initiatives.
- Contribute to thought leadership such as papers, innovative non-ML, ML, deep learning or LLM models, and proofs of concepts.
- Participate in and deliver analytics training, while contributing to content creation.
- Provide input for segment and unit-level business plans.
Your contribution to the team:
- Deliver scalable, high-quality analytics solutions aligned to business needs.
- A knack for optimization, deployment and performance improvement of models.
- The ability to drive innovation through advanced analytics, automation and thought leadership.
- Enable team growth through knowledge sharing, training and standardization.
- Support business planning with data-driven insights. Required Skill and Experience
- Hands-on experience in programming skills in Core Python
- Hands-on experience with MLOps, model deployment, CI/CD, and monitoring.
- Advanced Python development skills with experience in designing scalable ml systems, automations, sdk, multiprocessing etc.
- Experience with cloud services and Kubernetes.
- Hands-on with containerization, model optimization, and hardware acceleration.
- Solid understanding of data pipelines, feature stores, and ML model lifecycle.
- Implementation of MLOps tools like Grafana, Prometheus, Poetry, Snyk and others Preferred Skill and Experience
- Experienced in Agile way of working, manage team effort and track through JIRA
- Certifications in MLOps
- High Impact client communication
- Domain experience with Retail Clients Additional Required Qualifications
- Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
- This position may require relocation and/or travel to work/project location.
- All applicants authorized to work in the United States are encouraged to apply.