Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 12 days ago

Lead Machine Learning Engineer

Workable (global search)108,016 open roles

Where
Bengaluru, KA, India
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowLead Machine Learning EngineerWorkable (global search) · Bengaluru, KA, India

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Workable (global search)'s own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 12 days ago

Workable (global search) median: 7 days open

The posting

This role is for one of Weekday’s clients

Min Experience: 9+ years Location: Bengaluru JobType: full-time

We are seeking a hands-on Lead Machine Learning Engineer to design, build, and scale production-grade Generative AI and Machine Learning applications. The role will focus on developing AI-powered assistants, retrieval and reasoning systems, agentic workflows, document intelligence, decision-support solutions, and intelligent automation capabilities that improve productivity, service quality, customer experience, and business outcomes.

This is a technical leadership role for an engineer who has moved beyond experimentation and prototypes and has proven experience taking AI applications through the last mile into production. You will be responsible for ensuring AI systems are reliable, observable, secure, cost-efficient, measurable, and trusted by users.

You will work closely with Product, Engineering, Design, Security, Compliance, Operations, and business stakeholders to identify high-impact AI opportunities, make pragmatic architecture decisions, and deliver production-ready AI experiences at scale.

Requirements

Key Responsibilities

Build AI Solutions for Business Impact

  • Design, build, and launch GenAI-powered applications including AI assistants, copilots, document intelligence, workflow automation, and decision-support solutions.
  • Identify high-impact opportunities where AI can improve productivity, operational efficiency, service quality, customer experience, and business outcomes.
  • Take AI applications from concept through production, collaborating with Product, Engineering, Design, Security, and business teams.
  • Lead hands-on technical execution across application architecture, model selection, prompt engineering, retrieval, orchestration, APIs, data pipelines, and user-facing experiences.
  • Translate business requirements into scalable and measurable machine learning and AI solutions.
  • Establish success metrics and continuously optimize solutions based on real-world user feedback and business impact.

Build Enterprise-Grade AI Systems

  • Architect reliable GenAI applications using modern approaches such as RAG, agentic workflows, tool use, structured outputs, retrieval, grounding, and fine-tuning where appropriate.
  • Design systems that effectively combine frontier models, open-source models, smaller task-specific models, and deterministic components based on the specific use case.
  • Develop strong grounding mechanisms using enterprise knowledge and relevant business data.
  • Build production systems with appropriate observability, monitoring, versioning, fallback mechanisms, security, privacy, and operational ownership.
  • Design for reliability, scalability, latency, cost efficiency, and maintainability.
  • Stay current with advances in AI/ML and apply emerging techniques pragmatically where they deliver meaningful improvements.

Evaluation, Quality & LLMOps

  • Define practical evaluation frameworks for GenAI applications covering accuracy, relevance, groundedness, safety, latency, cost, user trust, adoption, and business impact.
  • Establish automated and human-in-the-loop evaluation processes for AI applications.
  • Use LLM evaluation and observability platforms such as LangFuse, Arize, or similar tools.
  • Monitor production performance and identify opportunities to improve model quality, reliability, and efficiency.
  • Establish appropriate safeguards, fallback paths, and quality controls for production AI systems.

Technical Leadership

  • Provide technical leadership across the AI/ML application development lifecycle.
  • Make pragmatic architecture and technology decisions while balancing quality, speed, security, and cost.
  • Mentor engineers and contribute to engineering standards, best practices, and technical direction.
  • Partner with cross-functional teams to ensure AI solutions are usable, secure, reliable, and aligned with business objectives.
  • Take ownership of production outcomes, including launch quality, reliability, user feedback, adoption, and measurable impact.

Required Experience & Qualifications

  • 8+ years of experience building applied AI/ML-based intelligent software systems.
  • 2+ years of practical Generative AI application experience.
  • At least one production GenAI application that has been deployed to real users at meaningful scale.
  • Proven experience taking GenAI solutions beyond PoC/prototype into production.
  • Strong ownership of production quality, reliability, cost optimization, user feedback, adoption, and measurable business impact.
  • Strong understanding of designing LLM applications using an appropriate combination of:
  • RAG
  • Agentic workflows
  • Tool use
  • Structured outputs
  • Retrieval and grounding
  • LLM orchestration
  • Frontier and open-source models
  • Fine-tuning
  • Task-specific models
  • Deterministic systems
  • Experience with modern AI application frameworks and LLMOps tools such as LangGraph, LangChain, LlamaIndex, and leading LLM APIs.
  • Strong programming and software engineering capabilities with the ability to build and deploy production-quality AI applications.
  • Experience using AI-native development tools such as Cursor, Claude Code, or similar tools is preferred, with strong judgment around code quality, security, and production reliability.

Good-to-Have Experience

  • GraphRAG
  • Long-context architectures
  • Model routing
  • Semantic and intelligent caching
  • Model cascades
  • PEFT / LoRA / QLoRA
  • Knowledge retrieval and grounding
  • Model distillation
  • Open-source model deployment
  • Advanced LLM evaluation and observability
  • Enterprise AI security and governance

Must-Have Skills

  • Machine Learning
  • Generative AI (GenAI)
  • Production AI/ML Systems
  • LLM Applications
  • Python / Software Engineering
  • AI Application Architecture

Good-to-Have Skills

  • End-to-End Production AI
  • Fine-Tuning
  • RAG
  • Agentic AI
  • LLMOps
  • LangGraph / LangChain / LlamaIndex
  • Model Evaluation & Observability
  • GraphRAG
  • PEFT / LoRA / QLoRA
From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against Workable (global search)'s own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on Workable (global search)'s form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    Workable (global search)'s answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.