Machine Learning Engineer Remote

work Full-time distance Remote payments $119,000 – $131,750 / yr

The Role

Cogniifyis hiring a Machine Learning Engineer (ML Engineer) to build the AI, LLM, and machine learning systems that sit at the center of our products.

You will design and own shared AI capabilities that many teams depend on, such as modeltraining pipelines, evaluation frameworks, and machine learning tooling. Youwill work closely with AI scientists, product managers, and designers, takingideas from a first proof of concept to a system running in production throughquick experiments and steady iteration.

Part ofthe work focuses on the foundations every AI product needs, like long-termmemory so an AI experience can keep context and personalize over time, an devaluation frameworks that make model quality and regressions easy to measureat scale. The rest is on the newer side of AI-native products, such as agentbuilder frameworks, generative AI built directly into product experiences, andagentic AI development.

This is aremote role based in the United States.

Coreskills for this role: Python, PyTorch, Tensor Flow, Pandas, Num Py, Large Language Models (LLMs), Generative AI, prompt engineering, fine-tuning,Lang Chain, Retrieval-Augmented Generation (RAG), AI agents, Kubernetes, and production machine learning systems.

What You Will Do

• Design and own shared AI and machine learning components,frameworks, and pipelines for model training, evaluation, and fine-tuning thatseveral product teams use.
• Use ML fundamentals and LLM techniques such as prompt engineering, fine-tuning, and Retrieval-Augmented Generation (RAG) to solvereal customer problems, and measure how the models perform in production.
• Prototype and build agent builder frameworks and AIexperiences that sit inside the product, taking agentic AI ideas from earlyexploration to something ready for users.
• Run fast prototypes and experiments to move from a proofof concept to accurate, well-performing production systems.
• Design and build AI-native applications end to end, frombackend services and APIs to LLM integrations in production.

What WeAre Looking For

• A BS, MS, or higher in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
• At least 5 years of experience building and deploying production AI and machine learning systems (experience leading an engineeringeffort is a plus).
• Strong computer science fundamentals including data structures, algorithms, and system design, along with solid machine learningfoundations such as classification, regression, clustering, and neural networks.
• Strong proficiency in Python and standard ML frameworks,including PyTorch, Tensor Flow, Pandas, and Num Py.
• Hands-on experience with Large Language Models (LLMs) and Generative AI, including prompt engineering, fine-tuning, RAG, and frameworks like Lang Chain.
• Experience building or running agentic AI systems, agentframeworks, or long-term memory and context architectures for AI applications.
• Familiarity with designing evaluation frameworks oroffline and online evaluation pipelines (LLMOps / MLOps) to measure the qualityof models and agents.
• A track record of launching AI integrations in production and measuring their real-world impact.
• Strong cross-functional collaboration skills, working well with data scientists, product managers, and software engineers across global teams.

Perksand Benefits of Working With Us

• Unlimited PTO
• Generous parental leave, well above industry standards
• Medical, dental, and vision coverage for employees
• Disability and life insurance
• Mental health and wellbeing support
• Employer Stock Purchase Program (ESPP)
• Yearly team-building experiences
• Mentorship and sponsorship opportunities
• Manager resources and support
• Small teams where your work makes a real difference
• Open communication with management and company leadership
• An entrepreneurial culture where taking initiative ispart of everyday work

Cogniify is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, orany other protected characteristic.