About the job
As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands-on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.
Responsibilities
Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.
Build and present compelling PoCs that demonstrate the capabilities of our AI technology.
Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.
Contribute to the internal ML platform, including adding features and resolving issues.
Integrate and enable new machine learning models into the existing platform or client environments.
Improve system performance, efficiency, and scalability of deployed models and applications.
Work closely with partners to enable joint AI solutions and ensure seamless collaboration.
Qualifications
Minimum
Bachelor’s degree in Computer Science, Engineering, or a related technical field.
5+ years of experience in a software engineering role, with a strong preference for customer-facing roles.
Robust coding skills required, preferably with proficiency in Python.
Demonstrated ability to lead and execute complex technical projects with a focus on customer success.
Strong interpersonal and communication skills; ability to thrive in dynamic, cross-functional teams.
Preferred
Master’s degree in Computer Science, Engineering, or a related technical field.
Experience working in a startup or fast-paced environment.
Hands-on experience fine-tuning machine learning models, including supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).
Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.