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Job Title


Lead Machine Learning Engineer


Company : Zemoso Technologies


Location : Pune, Maharashtra


Created : 2026-05-05


Job Type : Full Time


Job Description

Location - Chennai / Mumbai / Pune / Hyderabad / Bangalore (Hybrid)About UsZemoso Technologies is a Software Product Market Fit Studio that brings silicon valley stylerapid prototyping and rapid application builds to Entrepreneurs and Corporate innovation. Weoffer Innovation as a service and work on ideas from scratch and take it to the Product MarketFit stage using Design Thinking -> Lean Execution -> Agile Methodology.We were featured as one of Deloitte Fastest 50 growing tech companies from India thrice (2016,2018 and 2019). We were also featured in Deloitte Technology Fast 500 Asia Pacific both in2016 and 2018.We are located in Hyderabad, India, and Dallas, US. We have recently incorporated anotheroffice in Waterloo, Canada. Our founders have had past successes - founded a decisionmanagement company acquired by SAP AG (now part of Hana Big data stack & NetWeaverBPM), early engineering team of Zoho (leading billion $ SaaS player) & some Private Equityexperience. Marquee customers along with some exciting start-ups are part of our clientele.Role SummaryWe are seeking a highly experienced Machine Learning Lead to drive the architecture,development, and deployment of advanced machine learning solutions. In this role, you will notonly lead a talented technical team but also serve as the critical bridge between our engineeringefforts and our clients. You must possess the unique ability to distill complex, highly technicalML concepts into clear, business-driven language for stakeholders, ensuring the successfuldelivery of complex projects.What You Will Do● Stakeholder Communication & Client Management: Act as the primary technicalliaison for clients. Translate complex ML terms, model behaviors, and architecturaltrade-offs into actionable business insights for non-technical stakeholders.● Technical Leadership: Architect and design end-to-end ML solutions. Lead, mentor,and guide a team of Data Analysts and ML/Data Engineers through the entire projectlifecycle.● Project Delivery: Oversee the collection, cleanup, exploration, and statistical analysis ofcomplex datasets to drive business intelligence.● Model Lifecycle Management: Lead the implementation, deployment, and scaling ofadvanced ML models and algorithms to solve complex business problems.● Cross-functional Collaboration: Work closely with data engineers to design, build,test, and monitor robust data and MLOps pipelines for ongoing business operations.● Strategic Alignment: Understand the client's core business model to ensure the MLsolutions built bring measurable, actionable ROI out of data available in various formats.Basic Qualifications● Experience: 8 to 12 years of overall industry experience, with a proven track record inData Science, Machine Learning, and technical leadership.● Client-Facing Expertise: Demonstrated experience in stakeholder management,specifically the ability to confidently answer to clients and demystify complex MLconcepts in a consultative manner.● Technical Proficiency: Exceptional, hands-on coding experience in Python and robustexperience with popular ML frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch).● Analytical Rigor: Deep expertise in statistical modeling of large data sets and acomprehensive understanding of diverse ML algorithms.● Pipeline & Architecture: Strong experience designing robust data/ML pipelines andtransitioning models from experimentation to production environments.● Data Analytics: Solid foundational experience in data analytics, including the ability toextract actionable insights from raw data (experience with advanced Excel/BI tools is aplus).Nice to Have Qualifications● Hands-on experience with Deep Learning, Generative AI, or NLP frameworks.● Experience with MLOps practices and tools (e.g., MLflow, Kubeflow, Docker, Kubernetes).● Experience with Cloud platforms (AWS, GCP, or Azure) and their respective ML services.● A background working in fast-paced startup environments or consulting/services agencies.Benefits● Competitive salary.● Hybrid work model.● Learning and gaining experience rapidly.● Reimbursement for basic working set up at home.