This role is for one of the Weekday's clients
Min Experience: 8 yearsLocation: Bengaluru, Hyderabad, ChennaiJobType: full-timeThe 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
