AI/ML Software Engineer

Clutch; New York (NY); On-site; USD 150,000 - 200,000; Full time

Job summary

Clutch is seeking an experienced AI/ML Software Engineer to own the end-to-end machine learning lifecycle, from model optimization to deployment, in a flat startup culture.

You will tackle last-mile AI challenges, scale production pipelines, and own significant technical decisions while shaping a foundational platform for an early-stage venture in NYC.

Qualifications

• 5+ years of professional software engineering experience with growing scope and ownership.
• Expertise in AI/ML engineering with production-grade LLM orchestration and vector databases.
• Experience building automated validation and test pipelines for ML workloads.
• Strong communication, judgment, and ability to work in startup environments.

Responsibilities

• Design and scale automated ML pipelines, including LLM orchestration and vector searches.
• Develop automated evaluation frameworks and rigorous metrics for models.
• Investigate bias and ensure interpretability in high-throughput production systems.
• Advance core research intelligence engines with cross-functional collaboration.
• Make high-impact technical decisions independently in a lean, high-trust team.

Skills

AI/ML engineering

Model optimization

Automated validation

High-throughput data processing

Strong communication

Tools

LLM orchestration

Vector databases

Job description

Location: Flatiron District, New York, NY (Must be located in NYC and authorized to work in the US)

Hybrid/On-site/Remote: On-site (5 days weekly, with occasional Friday WFH flexibility)

Compensation: $150,000 – $200,000 base salary + meaningful early-stage equity and ownership

Clutch is looking for an experienced L5/L6 AI/ML Software Engineer for a client of ours—an innovative, early-stage technology company based in the Flatiron District. We are seeking a rigorous engineer with great product taste and a track record of scaling production systems, who is eager to shape core research intelligence platforms from the ground up.

About the Opportunity

In this role, you will tackle the complex "last mile" challenges of artificial intelligence—transforming raw model outputs into reliable, reproducible, and explainable systems fit for high-stakes analytical environments. Your initial focus will cover model optimization, infrastructure scaling, and defining the end-to-end machine learning lifecycle (including automated data labeling, evaluation frameworks, and deployment pipelines). As the engineering organization expands, you will have the autonomy to carve out your area of deepest ownership.

Key Responsibilities

• Model Lifecycle & Infrastructure: Design, build, and scale automated ML pipelines, model fine-tuning workflows, vector search architectures, and LLM orchestration layers for production environments.
• Evaluation & Rigor: Establish sophisticated, automated evaluation frameworks, treating model metrics with the same exactitude and testing standards applied to traditional software code.
• Interpretability & Debugging: Investigate, debug, and mitigate black-box behaviors, addressing model bias and ensuring interpretability in high-throughput production systems.
• Core Systems Evolution: Advance proprietary research intelligence engines, collaborating closely with cross-functional leaders to shape product roadmaps and architecture.
• Ambiguity & Ownership: Navigate open-ended problem spaces with strong judgment, making high-impact technical decisions independently within a high-trust, lean team.

Candidate Requirements

• 5+ years of professional software engineering experience demonstrating progressively expanding technical scope and individual ownership.
• Specialized expertise in AI/ML engineering, with production-level background in LLM orchestration, model fine-tuning, vector databases, and evaluation metrics.
• Demonstrated mastery in constructing automated validation and test pipelines for machine learning workloads.
• A strong foundation in modern AI frameworks and high-throughput data processing libraries (prior fintech or quant experience is welcome, but curiosity and engineering rigor are what truly matter).
• Exceptional communication skills, excellent judgment, and comfort operating in fast-moving, ambiguous startup environments.

What You Will Experience

• Direct, unfiltered exposure to core business strategy, product evolution, and customer engagement.
• A collaborative culture comprised of peers who hold exceptionally high standards for craft and engineering quality.
• The rare opportunity to build a foundational platform and equity stake in an early-stage venture.

Please read:

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