ML Engineer at Weekday AI

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

11 Jan, 26

Salary

0.0

Posted On

13 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning Engineering, Python, PyTorch, TensorFlow, JAX, LLM APIs, Data Processing, Model Optimization, Scalable Architectures, Rapid Experimentation, AI Systems, Natural Language Understanding, Marketing Automation, CI/CD Pipelines, Reinforcement Learning, User Experience, Feedback Loops

Industry

technology;Information and Internet

Description

This role is for one of Weekday’s clients JobType: full-time We’re looking for a Machine Learning Engineer to join as an early team member and help shape the foundation of our AI-powered platform. You’ll work directly with the founding team — serial entrepreneurs with a track record of building and exiting successful startups — to design, build, and scale real-world AI systems that transform how global brands approach marketing. This isn’t a “maintenance” role — it’s a builder’s role. You’ll have full ownership of the machine learning infrastructure, from data ingestion and model training to deployment and optimization. You’ll work on cutting-edge problems around LLMs, embeddings, reasoning frameworks, and feedback loops, developing systems that continuously learn and improve through user interactions. If you thrive in zero-to-one environments, love rapid experimentation, and want to see your work make a direct business impact, this is the place for you. Key Responsibilities Own the ML lifecycle end-to-end — from data pipelines and model design to deployment, monitoring, and optimization in production. Build, fine-tune, and scale LLM-based systems using APIs and open-source frameworks for natural language understanding, summarization, and reasoning. Develop and maintain embeddings, feedback loops, and decision engines that power intelligent marketing automation. Collaborate with product, design, and engineering teams to translate user problems into ML-driven solutions. Prototype quickly and iterate fast, applying real-world feedback to improve performance and accuracy. Implement best practices in data versioning, model validation, and CI/CD pipelines for ML workflows. Optimize ML models for performance, latency, and scalability across distributed systems. Stay ahead of industry trends in AI agents, reinforcement learning, and applied ML in marketing. What You Bring 3–5 years of hands-on experience in machine learning engineering or applied AI development. Strong proficiency in Python, with experience using PyTorch, TensorFlow, or JAX. Experience with LLM APIs (OpenAI, Anthropic, Hugging Face, etc.) and building products powered by foundation models. Proven track record of building and shipping ML systems to production — not just research or notebooks. Deep understanding of data processing, model optimization, and scalable architectures. Ability to work independently in fast-paced, ambiguous environments. A growth mindset — curiosity, experimentation, and an obsession with learning new technologies. Bonus Skills Experience with AI agent systems or reasoning frameworks. Background in eCommerce, martech, or personalization engines. Understanding of UX/design-driven development and how AI can elevate user experience. Familiarity with vector databases, LangChain, and retrieval-augmented generation (RAG) frameworks.

Responsibilities

Own the ML lifecycle end-to-end, from data pipelines and model design to deployment, monitoring, and optimization in production. Build and scale LLM-based systems while collaborating with product, design, and engineering teams to create ML-driven solutions.