Machine Learning Engineer
LTIMindtree - tampa, FL
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About Us:LTIMindtree is a global technology consulting and digital solutions company that enables enterprises across industries to reimagine business models, accelerate innovation, and maximize growth by harnessing digital technologies. As a digital transformation partner to more than 700+ clients, LTIMindtree brings extensive domain and technology expertise to help drive superior competitive differentiation, customer experiences, and business outcomes in a converging world. Powered by nearly 90,000 talented and entrepreneurial professionals across more than 30 countries, LTIMindtree "” a Larsen & Toubro Group company "” combines the industry-acclaimed strengths of erstwhile Larsen and Toubro Infotech and Mindtree in solving the most complex business challenges and delivering transformation at scale. For more information, please visit Title: Machine Learning Ops EngineerWork Location:Tampa, FLJob DescriptionDesign the data pipelines and engineering infrastructure to support our clients' enterprise machine learning systems at scaleTake offline models data scientists build and turn them into a real machine learning production systemDevelop and deploy scalable tools and services for our clients to handle machine learning training and inferenceIdentify and evaluate new technologies to improve performance, maintainability, and reliability of our clients' machine learning systemsApply software engineering rigor and best practices to machine learning, including CICD, automation, etc.Support model development, with an emphasis on auditability, versioning, and data securityFacilitate the development and deployment of proof-of-concept machine learning systemsCommunicate with clients to build requirements and track progressExperience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)Strong software engineering skills in complex, multi-language systemsFluency in PythonComfort with Linux administrationExperience working with cloud computing and database systemsExperience building custom integrations between cloud-based systems using APIsExperience developing and maintaining ML systems built with open source toolsExperience developing with containers and Kubernetes in cloud computing environmentsFamiliarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)Ability to translate business needs to technical requirementsStrong understanding of software testing, benchmarking, and continuous integrationExposure to machine learning methodology and best practicesExposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)Education & Experience5-10 years' experience building production-quality software.Bachelor's or master's degree andor equivalent professional experience.Benefitsperks listed below may vary depending on the nature of your employment with LTIMindtree ("LTIM"):Benefits and Perks:Comprehensive Medical Plan Covering Medical, Dental, VisionShort Term and Long-Term Disability Coverage401(k) Plan with Company matchLife InsuranceVacation Time, Sick Leave, Paid HolidaysPaid Paternity and Maternity LeaveThe range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location and job level and additional factors including job-related skills, experience, and relevant education or training. Depending on the position offered, other forms of compensation may be provided as part of overall compensation like an annual performance-based bonus, sales incentive pay and other forms of bonus or variable compensation.Disclaimer: The compensation and benefits information provided herein is accurate as of the date of this posting.LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.
Created: 2024-09-26