Data and Machine Learning Engineer

This role is for one of the Weekday's clientsMin Experience: 8 years

Location: Bengaluru, Hyderabad, Chennai

JobType: full-time

The Data & Machine Learning Engineer will design, build, and deploy scalable AI systems that power content automation, intelligent recommendations, and compliance-focused workflows. This role requires deep expertise in large language models (LLMs), retrieval-augmented generation (RAG), and production-grade ML pipelines, along with the ability to take solutions from concept through deployment and ongoing optimization.

Requirements

Key Responsibilities

AI & Model Development

• Integrate, fine-tune, and deploy large language models and image-generation models for AI-assisted content workflows.
• Build, optimize, and productionize RAG pipelines, including chunking strategies, embeddings, vector stores, and retrieval evaluation.
• Design AI systems to analyze, synthesize, and classify complex marketing and content assets.
• Implement AI-driven content and asset recommendations using metadata, business rules, and structured data.

Data & ML Engineering

• Architect and maintain scalable data and ML pipelines for structured and unstructured data.
• Build ingestion, validation, transformation, and schema enforcement pipelines.
• Develop and manage end-to-end AI content generation workflows, including prompt engineering, metadata tagging, and output formatting.
• Implement automated quality, safety, and compliance checks such as semantic filtering, claim matching, and risk scoring.

Platform & Production Systems

• Design and support production ML stacks using Python, FastAPI, and cloud-native services.
• Integrate AI pipelines with backend services and frontend applications built with modern web frameworks.
• Manage orchestration and scheduling of ML workflows using tools such as Airflow.
• Optimize performance, reliability, and scalability of deployed AI systems.

Cross-Functional Collaboration

• Collaborate with frontend engineers to define APIs and data contracts for rendering AI-generated assets.
• Work closely with data, product, and compliance stakeholders to ensure AI outputs align with business and regulatory requirements.
• Support live systems post-deployment and continuously improve models and pipelines.

Required Qualifications & Experience

• 8+ years of experience in machine learning or AI engineering, with a strong focus on LLMs and model deployment.
• Proficiency in Python, SQL, and ML frameworks such as TensorFlow and PyTorch.
• Hands-on experience with cloud platforms (preferably Azure) and Linux-based environments.
• Proven experience building scalable ML and RAG pipelines, including vector databases and retrieval systems.
• Experience with orchestration tools such as Airflow.
• Strong understanding of relational and vector databases, metadata systems, and data cataloging.
• Experience integrating ML systems with REST APIs and backend services (FastAPI preferred).
• Solid knowledge of NLP, embeddings, and retrieval-augmented generation techniques.
• Familiarity with compliance automation and risk mitigation for AI-generated content.

Preferred / Nice-To-Have Skills

• Experience with data platforms and tools such as Hadoop, Hive, Spark, or Snowflake.
• Familiarity with ComfyUI and multimodal content generation workflows.
• Exposure to frontend technologies such as React.js or similar frameworks.
• Experience with automated evaluation, safety, and governance for AI systems.
• Prior work in regulated or compliance-heavy domains.

Education

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field, or equivalent professional experience.

Key Attributes

• Ability to independently drive projects from concept to production and ongoing maintenance.
• Strong problem-solving mindset with a focus on scalable, reliable systems.
• Comfortable working in fast-paced, cross-functional environments.
• High ownership and accountability for production ML systems.