Founding ML Engineer (26-00082) -

Founding Machine Learning Engineer (AI/LLM)

Early-Stage AI Startup | $1M Pre-Seed Funding | Founding Team

Location

San Francisco Bay Area or New York City

Company Stage

Pre-Seed | $1M Raised

Tech Stack

Python, AWS, PostgreSQL, MongoDB, LLMs, NLP, Applied ML

About the Opportunity

We're partnering with an ambitious, recently funded AI startup that's tackling one of the most important challenges in enterprise

AI

making AI-powered interactions more accurate, reliable, and trustworthy at scale.

As businesses rapidly adopt AI agents to handle customer interactions, the need for sophisticated systems that can evaluate performance, detect errors, and ensure quality is growing exponentially. This startup is building technology to address that challenge, helping enterprises confidently deploy AI in complex, high-stakes environments.

With $1 million in pre-seed funding, an early product already in production, and real enterprise design partners, the company is at an exciting inflection point. The founding team is small, highly technical, and focused on building a category-defining platform in a rapidly expanding market.

This is an opportunity to get in at the ground floor, influence the company's technical direction, and play a foundational role in building both the product and engineering organization.

The Role

We're looking for a Founding Machine Learning Engineer to take ownership of the company's core ML and AI intelligence systems.

As the first dedicated ML hire, you'll work directly with the CTO to design, build, and scale the technology that evaluates AI-generated interactions for accuracy, quality, and reliability.

This isn't a research-only position or a role where you'll simply maintain existing models. You'll be a hands-on technical leader with significant autonomy, responsible for making critical architectural decisions, shipping production systems, and establishing the ML practices that will support the company's growth.

You'll join at a particularly exciting stage

the company already has a working production pipeline and real-world customer data, giving you the opportunity to make an immediate impact rather than starting from scratch.

As the organization scales, you'll also have the opportunity to build and lead the ML engineering team, shaping the technical culture and standards from the beginning.

What You'll Do

Own the Core ML Architecture

• Design and develop intelligent systems that evaluate AI-generated interactions for accuracy, hallucinations, quality, and potential risk.
• Build scalable detection and scoring frameworks using LLMs, classifiers, rules-based systems, and other ML approaches.
• Make strategic decisions about model selection, performance, accuracy, cost, and latency.
• Develop robust, production-ready ML services that can operate reliably at enterprise scale.

Build a World-Class Evaluation Framework

• Establish evaluation methodologies, benchmarks, and regression testing to ensure consistent model performance.
• Build pipelines for data annotation, ground-truth development, and continuous model improvement.
• Develop feedback loops that transform real-world customer interactions into actionable training and evaluation data.
• Implement rigorous measurement practices to ensure model accuracy is demonstrated, not assumed.

Accelerate Product Development

• Build tools and workflows that make it faster to adapt ML systems to new enterprise customers and use cases.
• Develop active-learning processes, reusable datasets, and automated evaluation capabilities.
• Collaborate directly with the founding team and early customers to translate complex requirements into scalable technical solutions.
• Help define the ML roadmap and identify opportunities for technical differentiation.

Solve Complex Speech and Language Challenges

• Improve the reliability of evaluating noisy, unstructured conversational data.
• Assess and integrate speech recognition, transcription, and speaker-identification technologies as the platform evolves.
• Develop approaches for analyzing complex interactions across multiple communication channels.

Scale the Technology and Team

• Optimize inference infrastructure for performance, reliability, and cost efficiency.
• Build monitoring systems to identify model drift, accuracy degradation, and emerging issues.
• Establish engineering best practices for production ML development and deployment.
• Help recruit, mentor, and eventually lead future ML engineers as the company grows.

What We're Looking For

We're seeking an exceptional, hands-on ML engineer who combines deep technical expertise with the entrepreneurial mindset needed to thrive in an early-stage startup.

Required Qualifications

• Significant experience in applied Machine Learning, NLP, or LLM engineering, ideally operating at a Staff, Principal, or equivalent technical level.
• Proven experience designing, building, and deploying ML or LLM systems in production.
• Strong Python engineering skills and the ability to own production services end to end.
• Deep understanding of model evaluation, accuracy measurement, and building reliable ML systems.
• Experience working with LLMs, including techniques such as prompting, retrieval, fine-tuning, distillation, and model-based evaluation.
• Ability to navigate trade-offs between model performance, latency, infrastructure costs, and business requirements.
• Experience working with unstructured data, annotation workflows, and imperfect real-world datasets.
• Prior startup experience, with demonstrated success operating in fast-moving environments with limited infrastructure and significant ambiguity.
• Strong product instincts and the ability to translate business challenges into practical technical solutions.
• Interest in remaining deeply hands-on while helping build an engineering organization from the ground up.

Nice to Have

• Experience with speech or audio ML, including automatic speech recognition (ASR), speaker diarization, or streaming transcription.
• Experience building custom NLP models, scoring systems, or LLM-as-judge frameworks.
• Familiarity with weak supervision, active learning, or programmatic data labeling.
• Background in AI trust and safety, fraud detection, risk assessment, enterprise compliance, or customer experience technology.
• Experience supporting enterprise AI deployments involving sensitive data, security, or governance requirements.
• Familiarity with AWS, PostgreSQL, or MongoDB.

Why Join?

Get in at the ground floor. Join a recently funded, pre-seed startup where your work will directly influence the company's product, technology, and trajectory.

Own something meaningful. As the first dedicated ML engineer, you'll have the autonomy to make foundational technical decisions rather than inherit someone else's roadmap.

Build in one of AI's fastest-evolving markets. Help solve the challenges that emerge as enterprises move beyond AI experimentation and deploy autonomous systems into real-world business operations.

Work directly with the founders. Collaborate closely with a small, highly technical team where decisions happen quickly and individual contributions have an outsized impact.

Shape the future engineering team. Establish the technical foundation, influence hiring decisions, and grow into broader technical leadership as the company scales.

Solve hard problems with real-world impact. Work on complex ML challenges involving evaluation, hallucination detection, language understanding, model reliability, and production optimization, with access to real customer data from day one.

Who Will Thrive Here?

You'll love this opportunity if you're the kind of engineer who wants to build, not just advise.

You're comfortable making decisions without perfect information, enjoy solving ambiguous technical problems, and care deeply about shipping systems that actually work.

You might be a Staff or Principal ML Engineer at a larger organization who's ready for more ownership, or a senior technical leader at a startup who wants to help build the next company from its earliest days.

Above all, you're excited by the opportunity to build foundational AI technology, work alongside an ambitious founding team, and help turn an early-stage product into a scalable business.

If you're looking for a role where your technical decisions, creativity, and execution can make a defining difference, we'd love to connect.

From Tangerine Search

Tangerine Search is an equal opportunity agency that values diversity. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment.