Staff Machine Learning Engineer

About Andela:

At Andela, we know brilliance is evenly distributed around the world, but opportunity is not. For over 10 years, Andela has connected its customers with top global, remote technical talent from over 135 countries with the majority residing in emerging markets like Africa and Latin America.

As one of the world’s largest talent marketplaces, Andela gives companies greater flexibility to quickly deploy qualified technologists. With talent highly skilled in advanced technologies to support Application Development, Artificial Intelligence, Cloud & DevOps, Data Engineering, and much more, customers experience 33% faster project delivery. The company’s exclusive AI-powered platform, Andela Talent Cloud, is the industry’s only unified platform managing the complete global talent lifecycle and enables customers to fill individual roles or engage fully managed teams up to 66% faster.

Andela is on the precipice of two breakout industry transformations: one in staffing/hiring and the other in software development, both accelerated by generative AI.

Join us and change the world.

Job Summary:

We are seeking a Staff Machine Learning Engineer to join our dynamic team specializing in a technology marketplace platform for engineering talent and delivering cutting-edge Generative AI (GenAI) managed solutions for enterprise clients. 

In this strategic role, you will be responsible for designing, developing, and deploying scalable machine learning algorithms and systems. Your proven experimental mindset and extensive practical experience will be key in optimizing our platform’s performance, improving our GenAI offerings, and driving measurable impact across diverse business use cases.

Exceptional Leadership:

As an Andelan, you don’t need to be a people manager to be a leader, and you’ll serve as a role model for the rest of the company. Think about the feedback your peers typically give you – if it usually sounds like the below, we want to hear from you. 

• Low ego, low drama, servant leader: You share credit, take blame. You like being wrong because it means someone else had an even better idea. 

• One team mentality: You break silos across teams. You put the company and mission first above yourself and team alone. 

• Great listener, hungry for feedback: You’re always seeking to improve – our product, our business, yourself. You solicit diverse opinions and deeply listen. 

• Owner, not renter: You see a problem, you fix it or find someone who will. The buck stops with you.

• Player-coach: You roll up your sleeves and get scrappy. You do this by proactively collaborating with your team while actively engaging in important details. 

• Business problem solver: You’re not just a functional expert; you consistently get praise for approaching your function through the lens of solving business problems. 

Key Responsibilities:

• Design, build, and maintain robust and scalable machine learning models and pipelines tailored to enhance our marketplace platform and GenAI managed solutions.

• Lead experimentation processes, rigorously validating models through A/B testing, statistical analyses, and iterative improvements.

• Collaborate closely with data scientists, software engineers, product managers, and client teams to define requirements, build solutions, and deliver impactful, high-quality products.

• Continuously improve existing ML solutions, ensuring they are performant, efficient, and aligned with evolving business objectives.

• Ensure adherence to best practices in code quality, data integrity, and infrastructure reliability, with a strong emphasis on scalability and maintainability.

• Mentor junior engineers and contribute actively to team growth, knowledge sharing, and fostering an experimental, innovation-driven engineering culture.

• Stay current with advancements in machine learning, AI methodologies, and marketplace technologies to propose innovative solutions proactively.

Qualifications:

• Bachelor’s degree or higher in Computer Science, Engineering, Data Science, or a related technical field.

• Proven experience implementing machine learning algorithms and solutions at scale in production environments.

• Demonstrated experimental mindset, adept at hypothesis testing, experimentation design, and rigorous validation techniques.

• Expert proficiency in Python an