Job Details
JOB DESCRIPTION As a Manager/Senior Manager for MLOps, you will manage multiple projects of varying complexity and ensure on-time and on-budget delivery for clients He/ she will lead a team working across cross-functional groups, while contributing to new business development, supporting strategic business decisions and maintaining & strengthening client base As an individual contributor, you will leverage your technical skills, business acumen and creativity to analyse business problems, build collaterals to support the sales call, do market research on the new leads, build point of views for the problems statements and execute proof of concepts and pilots The ideal candidate is deeply analytical and detailed-oriented and capable of thinking independentlyTHE IDEAL CANDIDATE WILL Engage with executive level stakeholders from client's team to translate business problems to high level solution approach Partner closely with practice, and technical teams to craft well-structured comprehensive proposals/ RFP responses clearly highlighting Tredence's competitive strengths relevant to Client's selection criteria Actively explore the client's business and formulate solution ideas that can improve process efficiency and cut cost, or achieve growth/revenue/profitability targets faster Work hands-on across various MLOps problems and provide thought leadership Grow and manage large teams with diverse skillsets Collaborate, coach, and learn with a growing team of experienced Machine Learning Engineers and Data ScientistsELIGIBILITY CRITERIA BE/BTech/MTech (Specialization/courses in ML/DS) At-least 7+ years of Consulting services delivery experience Very strong problem-solving skills & work ethics Possesses strong analytical/logical thinking, storyboarding and executive communication skills 5+ years of experience in Python/R, SQL 5+ years of experience in NLP algorithms, Regression & Classification Modelling, Time Series Forecasting Hands on work experience in DevOps Should have good knowledge in different deployment type like PaaS, SaaS, IaaS Exposure on cloud technologies like Azure, AWS or GCP Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
Knowledge of Deep Learning frameworks: Keras, Tensorflow, PyTorch, etc Experience with one or more Container-ecosystem (Docker, Kubernetes) Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint Good understanding of OOP & Data Structures conceptsNice to Have: Exposure to deployment strategies like: Blue/Green, Canary, AB Testing, Multi-arm Bandit Experience in Helm is a plus Strong understanding of data infrastructure, data warehouse, or data engineering