Software Engineer 2 , Machine Learning

Interview Kickstart; United States; Remote; USD 150,000 - 230,000; Full time

Benefits offered by this job

Permanent remote work

Job summary

Interview Kickstart is seeking an AI-focused professional to tackle real-world problems using statistical modeling, ML, and generative AI/LLMs. You will design and implement AI-powered solutions, including agent systems with LangChain and various APIs, and collaborate with product teams to drive learner outcomes.

You will deploy these models in scalable production environments on cloud platforms, stay current with AI advancements, and contribute to robust evaluation frameworks.

Qualifications

• Proven experience building statistical and ML models across traditional and deep learning methods.
• Hands-on experience with AI agents and multi-step workflows.
• Strong prompt engineering and practical deployment skills.

Responsibilities

• Collaborate with product managers and stakeholders to translate business challenges into ML problems and actionable requirements.
• Research and design ML solutions using statistical modeling and generative AI/LLMs.
• Work with ML engineers to develop, refine, and deploy AI solutions in production on cloud platforms (AWS/Azure/GCP).
• Build and evaluate agent pipelines, tests for agent behaviors, and evaluation frameworks.

Skills

Statistical modeling

Machine learning

Generative AI/LLMs

Prompt engineering

Tools

LangChain

LangGraph

OpenAI API

Gemini API

Anthropic API

Pinecone

Weaviate

AWS/Azure/GCP

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