Machine Learning Engineer

Remote

Job Description

This job posting has expired and no longer accepting applications.

Who We Are:

AI Fund is a venture studio that works with entrepreneurs to build companies rapidly and increase the odds of success. Backed with $300m from Greylock, NEA, Sequoia and other LPs, and spearheaded by Andrew Ng (Co-Founder of Coursera, Co-Founder/Head of Google Brain), we’re partnering with our CEOs to build the next generation of AI tech companies.

What You Will be Doing:

We are currently seeking an exceptionally talented Machine Learning Engineer to join our technical team. You will be responsible for the end-to-end ownership of scalable machine learning systems—from translating business ideas into actionable technical solutions, to building data pipelines, training models, and analyzing performance in a production environment. You will be joining a team that leads the development from Proofs of Concept (PoCs) to initial production pipelines in early-stage startups. You must be adaptable, able to assume multiple roles, and thrive in a dynamic environment.

Main Responsibilities:

Design and Develop Production-Ready Solutions: Lead the development of new machine learning models focused on transforming a wide variety of datasets and use cases into actionable insights. Apply fundamental machine learning concepts to iterate quickly, debug model-related issues, and develop innovative techniques to handle unique cases for each customer.

Collect, Process, and Analyze Data: Understand and analyze data as a critical component of our machine learning projects. Build pipelines and processes for data cleaning and organization, and develop tools to facilitate data analysis. Identify areas where models are underperforming and propose effective solutions based on your analysis.

Stay Current with Advances in Machine Learning and Generative AI: Keep up-to-date with the state of the art in machine learning and generative AI. Continuously integrate relevant advancements into our models and workflows to maintain a cutting-edge technological edge.

What You Must Bring:

Experience: Minimum of 3 years of professional experience in designing, training, and deploying machine learning models.

Technical Expertise:

Strong foundation in computer science, including data structures, algorithms, and design patterns.

Expertise in Python, demonstrated by implementing multiple medium to large-scale projects.

Proven ability to implement and debug machine learning models.

Familiarity with machine learning frameworks and libraries (e.g., scikit-learn, PyTorch, MLFlow).

Experience in setting up data pipelines.

Experience in developing RESTful APIs.

Proficiency in cloud platforms (AWS, GCP) and containerization technologies.

Industry experience with relational databases, SQL, and NoSQL tools.

Experience with commercial and open-source Large Language Models (LLMs) and frameworks such as LangChain and LlamaIndex.

Education: Bachelor’s degree in Computer Science, Mathematics, or a related field.

Nice to Haves:

Experience with agentic frameworks such as LangGraph and crewAI.

Experience designing and deploying retrieval augmented generation (RAG) systems into production.

Research experience in machine learning or artificial intelligence.

Contributions to open-source machine learning projects.

Experience with Agile development methodologies.

Master's or Ph.D. degree in a relevant field is a plus.

Soft Skills:

Excellent communication skills with the ability to engage in in-depth technical discussions with both engineering teams and business stakeholders.

Proficiency in English.

Self-starter with the ability to work comfortably in an early-stage environment.

Characteristics:

Accountability: an obligation or willingness to accept responsibility or to account for one's actions while doing so with the highest regard for integrity.

Leadership: able to influence others to follow you and lead the team to a brighter future.

Grit: able to stick with projects and work hard through good and bad times. High pain tolerance and can perform well under stress or pressure.

Scrappy: Takes initiative and proactively gets things done with low resources, but doing creative things, begging, borrowing, and whatever is needed in an ambiguous environment or situation.

Ownership orientation: Demonstrated orientation of extreme ownership over all aspects of the company and extremely results-driven in nature

At AI Fund, we are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants without regard to race, color, religion, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by applicable law. AI Fund believes that diversity and inclusion among our employees is critical to our success as a company, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool. Selection for employment is decided on the basis of qualifications, merit, and business need.

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