Software Engineer 2, Machine Learning

Interview Kickstart

. Collaborate with product managers and business stakeholders to understand business challenges and translate them into machine learning problems and actionable project requirements.

Posted 11/5/2026full-timeRemote • IndiaJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in machine learning model development, statistical modeling, and deploying AI solutions in scalable production environments. Proficient in collaborating with cross-functional teams to translate business challenges into actionable machine learning projects.

Highest-signal resume keywords

Machine Learning Model DevelopmentStatistical ModelingAI Agent DeploymentCloud Platforms (AWS, Azure, GCP)Prompt Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningStatistical ModelingDeep Learning TechniquesRegressionClassificationClusteringNeural NetworksCNNsRNNsDebugging

Soft Skills

Communication SkillsProblem-Solving Skills

Tools & Technologies

LangChainLangGraphOpenAI APIGemini APIAnthropic APIPineconeWeaviate

Industry Keywords

AI/MLGenerative AIEvaluation FrameworksAgent PipelinesSemantic Search

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud Platform

About the role

Key responsibilities & impact

Collaborate with product managers and business stakeholders to understand business challenges and translate them into machine learning problems and actionable project requirements.
Research and design solutions using statistical modeling, machine learning, and generative AI/LLMs.
Collaborate with machine learning engineers to develop and refine solutions.
Work with Applied AI/ML engineers to build LLM-powered agentic systems for real product use cases.
Design, develop, and optimize agent pipelines and APIs.
Build tests for agent behaviors and contribute to evaluation frameworks.
Deploy machine learning solutions into scalable production environments on cloud platforms such as AWS, Azure, and GCP.
Ensure deployed solutions are effective.
Stay informed about developments in AI/ML, publications, best practices, evaluation methodologies, technology stacks, and relevant tools.

Requirements

What you’ll need

2+ years of full-time experience as an ML engineer at tier-1 product-based companies.
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.
Good debugging and online searching skills.
Good communication skills.
Good problem-solving skills, including ability to solve hard-level data structures and algorithms problems.
Hands-on experience building and deploying AI Agents using LangChain, LangGraph, OpenAI API, Gemini API, Anthropic API, etc. (good to have).
Hands-on experience with multi-step agent workflows, orchestration, and evaluating agent reliability (good to have).
Hands-on experience with vector databases (Pinecone, Weaviate) and semantic search (good to have).
Hands-on experience fine-tuning open-weight language models and deploying and maintaining them in scalable production environments on cloud platforms such as AWS, Azure, or GCP (good to have).

Benefits

Comp & perks

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