Job Details

Overview

We are looking for an experienced Senior Data Scientist / ML Engineer with a strong blend of pre-sales expertise and technical proficiency across classical machine learning, deep learning, and generative AI. You will engage in high-level client discussions, drive technical sales strategies, and lead a team to design and implement cutting-edge ML solutions. This is a strategic role requiring both thought leadership and hands-on technical contributions.

Responsibilities

• Collaborate with the sales and business development teams to identify client needs and formulate AI/ML solutions.
• Present technical concepts, project proposals, and proof-of-concepts (POCs) to prospects and clients.
• Translate complex client requirements into actionable project scopes, estimates, and technical proposals.

Classical Machine Learning & Statistical Modeling

• Apply classical machine learning techniques (e.g., regression, clustering, decision trees, ensemble methods) to solve diverse business problems.
• Design and optimize data pipelines, feature engineering processes, and model selection strategies.
• Ensure robust model evaluation, tuning, and performance monitoring in production environments.
• Develop and maintain deep learning models using frameworks such as TensorFlow or PyTorch for tasks like computer vision, NLP, or recommendation systems.
• Explore and build solutions leveraging generative AI (GANs, VAEs, or transformer-based architectures) for innovative product features and services.
• Champion research and experimentation with state-of-the-art AI models, staying ahead of industry advances.

Project Delivery & MLOps

• Help lead end-to-end ML project lifecycles, from data exploration and model development to deployment and post-launch maintenance.
• Help implement MLOps best practices (CI/CD, containerization, model versioning) on cloud or on-premise infrastructures.
• Collaborate with DevOps and engineering teams to integrate ML solutions seamlessly into existing systems.

Required Qualifications

• Education & Experience
• Master's or PhD in Computer Science, Data Science, Engineering, or a related field is preferred.
• 6+ years of relevant industry experience in data science or ML engineering

Technical Expertise

• Pre-Sales: Demonstrated experience in client-facing roles, solutioning, and proposal development.
• Classical ML: Skilled in traditional algorithms (regression, classification, clustering, etc.) and statistical methods.
• Deep Learning: Hands-on expertise with frameworks (e.g., TensorFlow, PyTorch) for CNNs, RNNs, transformer architectures, etc.
• Generative AI: Practical exposure to GANs, VAEs, or large language models, with a track record of building generative models.
• MLOps: Familiarity with CI/CD pipelines, Docker/Kubernetes, and cloud platforms (AWS, Azure, GCP).

Preferred / Bonus Skills

• Experience in big data ecosystems (Spark, Hadoop) for large-scale data processing.
• Background in NLP, computer vision, or recommendation systems.
• Knowledge of DevOps tools (Jenkins, GitLab CI, Terraform) for infrastructure automation.
• Track record of published research or contributions to open-source AI projects.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Industries

• Software Development