Software Engineer 2 , Machine Learning

Interview

India

Remote

INR 1,800,000 - 2,600,000

Full time

14 days+

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Benefits offered by this job

Permanent remote / work-from-home

Job summary

Interview in India seeks a hands-on ML engineer to drive machine learning initiatives across product teams. You will translate business challenges into well-defined ML problems and build robust, scalable solutions that power learner experiences.

The role emphasizes AI-first approaches, generative AI/LLMs, and deploying models to cloud platforms. You will collaborate with a high-caliber team and stay current with AI developments.

Qualifications

  • Experience building statistical models and machine learning solutions.
  • Strong problem-solving and debugging abilities.
  • Good communication skills.

Responsibilities

  • Collaborate with product managers to translate business challenges into ML problems and requirements.
  • Research and design optimal ML solutions using statistical modeling, ML, and generative AI/LLMs.
  • Collaborate with ML engineers to deploy solutions and optimize agent pipelines in production.
  • Deploy ML solutions into scalable cloud environments (AWS/Azure/GCP) and ensure effectiveness.
  • Stay informed about AI/ML developments, evaluation methodologies, and tooling.

Job description

WHAT WILL EXCITE US?
  • MIMP: An AI-first approach for solving problems.
  • Hands-on experience building statistical and machine learning models, with proven expertise across traditional methods (regression, classification, clustering, tree-based models) and deep learning techniques (neural networks, CNNs, RNNs).
  • Solid prompt engineering skills.
  • Hands-on experience building and deploying AI Agents using LangChain, LangGraph, OpenAI API, Gemini API, Anthropic API, etc.
  • Hands-on experience with multi-step agent workflows, orchestration, and evaluating agent reliability.
  • Hands-on experience with vector databases (Pinecone, Weaviate) and semantic search.
  • Hands-on experience fine-tuning open-weight language models and successfully deploying and maintaining them in scalable production environments on cloud platforms (e.g., AWS, Azure, GCP).
  • Good debugging and online searching skills.
  • Good communication skills.
  • Good problem-solving skills (ability to solve hard-level data structures and algorithms problems).
WHAT WILL YOU BE DOING?
  • Collaborate closely with product managers and business stakeholders to gain a deep understanding of business challenges, translating them into well-defined machine learning problems and actionable project requirements that drive business growth and enhance learner experiences.
  • Leverage your expertise in statistical modeling, machine learning, and generative AI/LLMs to research and design optimal solutions for the identified machine learning problems.
  • Collaborate closely with machine learning engineers to develop and refine optimal solutions for the identified machine learning problems.
  • Closely work with Applied AI/ML engineers building LLM-powered agentic systems for real product use cases.
  • Design, develop, and optimize agent pipelines/APIs, build tests for agent behaviors, and contribute to evaluation frameworks.
  • Take ownership of deploying the developed machine learning solutions into scalable production environments (on cloud platforms like AWS, Azure, GCP) and ensure these deployed solutions are effective.
  • Staying informed about recent developments in AI/ML, including key publications, best practices, evaluation methodologies, technology stacks, and relevant tools.
WHY WILL YOU ENJOY WORKING WITH US?
  • Permanent remote / work-from-home culture
  • Opportunity to work on a cutting-edge AI technology stack
  • An AI-first approach to solving real-world problems
  • Complete ownership and trust from leadership
  • Your ideas and concerns are actively heard by the leadership team
  • Freedom to experiment, fail, and learn
  • Rapid career progression for high performers
  • Work with a high-caliber team of engineers and industry experts
  • Learn how a fast-growing startup builds and scales
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