[Hiring] Software Engineer 2, Machine Learning @Interview Kickstart

Role 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.

Benefits

• 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