Data and Machine Learning Engineer at Weekday AI

Chennai, tamil nadu, India -

Full Time

Start Date

Immediate

Expiry Date

23 Mar, 26

Salary

0.0

Posted On

23 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, AI Engineering, Large Language Models, Python, SQL, TensorFlow, PyTorch, Cloud Platforms, Linux, RAG Pipelines, Orchestration Tools, NLP, Embeddings, REST APIs, Compliance Automation, Data Cataloging

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Min 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. 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.

Responsibilities

The Data & Machine Learning Engineer will design, build, and deploy scalable AI systems for content automation and intelligent recommendations. Responsibilities include developing ML pipelines, integrating AI models, and collaborating with cross-functional teams.