Senior Machine Learning Engineer

Zemoso Technologies; Bengaluru Urban; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Zemoso Technologies seeks a highly experienced Machine Learning Lead to drive architecture, development, and deployment of advanced ML solutions. You will bridge engineering efforts and clients, translating complex ML concepts into business-focused language for stakeholders.

Responsibilities include leading a team of Data Analysts and ML/Data Engineers, overseeing data collection and model lifecycle management, and ensuring ROI through scalable data/ML pipelines and MLOps practices.

Qualifications

• 8–12 years of experience in Data Science, ML, and technical leadership.
• Client-facing expertise translating ML concepts to business terms for stakeholders.
• Proficiency in Python and ML frameworks (Scikit-Learn, TensorFlow, PyTorch).
• Deep expertise in statistical modeling of large data sets and various ML algorithms.

Responsibilities

• Lead the architecture, development, and deployment of advanced ML solutions.
• Bridge between engineering efforts and clients to deliver complex projects.
• Mentor and guide Data Analysts and ML/Data Engineers through project lifecycles.
• Oversee data collection, cleaning, exploration, and analysis for insights.
• Design and monitor robust data/ML pipelines and MLOps workflows.

Tools

Python

Scikit-Learn

TensorFlow

PyTorch

Statistical modeling

Data analytics

Excel

BI tools

MLflow

Kubeflow

Docker

AWS

GCP

Azure

Job description

We 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 not

only lead a talented technical team but also serve as the critical bridge between our engineering

efforts and our clients. You must possess the unique ability to distill complex, highly technical

ML concepts into clear, business-driven language for stakeholders, ensuring the successful

delivery of complex projects.

What You Will Do

• Stakeholder Communication & Client Management: Act as the primary technical liaison for clients. Translate complex ML terms, model behaviors, and architectural trade-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 project lifecycle.
• Project Delivery: Oversee the collection, cleanup, exploration, and statistical analysis of complex datasets to drive business intelligence.
• Model Lifecycle Management: Lead the implementation, deployment, and scaling of advanced 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 ML solutions 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 in Data 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 ML concepts in a consultative manner.
• Technical Proficiency: Exceptional, hands-on coding experience in Python and robust experience with popular ML frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch).
• Analytical Rigor: Deep expertise in statistical modeling of large data sets and a comprehensive understanding of diverse ML algorithms.
• Pipeline & Architecture: Strong experience designing robust data/ML pipelines and transitioning models from experimentation to production environments.
• Data Analytics: Solid foundational experience in data analytics, including the ability to extract actionable insights from raw data (experience with advanced Excel/BI tools is a

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,
• Experience with Cloud platforms (AWS, GCP, or Azure) and their respective ML services.
• A background working in fast-paced startup environments or consulting/services
• Learning and gaining experience rapidly.
• Reimbursement for basic working set up at home.