ML Engineer
$110k - $140kTata Consultancy Services
Must Have Technical/Functional Skills
- 1+ years of experience building, scaling, and optimizing ML systems
- 1+ years of experience with data gathering and preparation for ML models
- 2+ years of experience developing performant, resilient, and maintainable code
- Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
- 3+ years of experience with distributed file systems or multi-node database paradigms
- 3+ years of experience building production-ready data pipelines that feed ML models.
- Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
- Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
- Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).
- Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
- Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
- Retrain, maintain, and monitor models in production.
- Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
- Construct optimized data pipelines to feed ML models.
- Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
- Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
- Use programming languages like Python, Scala, or Java.
- Discretionary Annual Incentive.
- Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
- Family Support: Maternal & Parental Leaves.
- Insurance Options: Auto & Home Insurance, Identity Theft Protection.
- Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
- Time Off: Vacation, Time Off, Sick Leave & Holidays.
- Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
Vacancy posted 2 days ago
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