Machine Learning Engineer

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 www.ltimindtree.com.

Job Title: Machine Learning Ops Engineer

Work Location:

Tampa, FL

Job Description

• Design the data pipelines and engineering infrastructure to support our clients’ enterprise machine learning systems at scale
• Take offline models data scientists build and turn them into a real machine learning production system
• Develop and deploy scalable tools and services for our clients to handle machine learning training and inference
• Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients’ machine learning systems
• Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
• Support model development, with an emphasis on auditability, versioning, and data security
• Facilitate the development and deployment of proof-of-concept machine learning systems
• Communicate with clients to build requirements and track progress
• Experience 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 systems
• Fluency in Python
• Comfort with Linux administration
• Experience working with cloud computing and database systems
• Experience building custom integrations between cloud-based systems using APIs
• Experience developing and maintaining ML systems built with open source tools
• Experience developing with containers and Kubernetes in cloud computing environments
• Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)
• Ability to translate business needs to technical requirements
• Strong understanding of software testing, benchmarking, and continuous integration
• Exposure to machine learning methodology and best practices
• Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)

Education & Experience

• 5-10 years’ experience building production-quality software.
• Bachelor’s or master’s degree and/or equivalent professional experience.

Benefits/perks listed below may vary depending on the nature of your employment with LTIMindtree (“LTIM”):

Benefits and Perks:

• Comprehensive Medical Plan Covering Medical, Dental, Vision
• Short Term and Long-Term Disability Coverage
• 401(k) Plan with Company match
• Life Insurance
• Vacation Time, Sick Leave, Paid Holidays
• Paid Paternity and Maternity Leave

The 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.