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We’re looking for an AI Engineer who’s passionate about turning ideas into real-world, production-grade Machine Learning systems. This role is hands-on and technical - you’ll prototype, build, and deploy end-to-end Machine Learning solutions while applying best-in-class engineering, cloud, and MLOps practices. Whether you’re just starting out or already experienced, you’ll contribute to impactful projects, collaborate with clients, and grow your role over time. If you thrive at the intersection of AI, cloud, and real-world problem-solving, you’ll fit right in.
Job Responsibility:
Translate business challenges into ML opportunities - understand the “why” behind problems and propose solutions that matter
Experiment, train, and optimize models, including leveraging the latest in generative AI
Engineer for scale - ensure performance, reliability, and efficient use of compute resources
Build and maintain data pipelines & MLOps workflows, enabling fast and repeatable iteration cycles
Deploy ML solutions on AWS, GCP, or Azure, integrating seamlessly with production systems
Write clean, well-structured Python code following modern engineering and CI/CD best practices
Requirements:
1–3 years of experience in: AI or ML Engineering, or Software Engineering with a focus on AI/ML
Strong Python skills for backend development
Experience working with cloud platforms (Google Cloud, AWS, or Azure)
Hands-on software engineering experience
Solid understanding of SQL
Familiarity with ML deployment & web service integration (e.g., FastAPI)
Nice to have:
Experience in consulting or client-facing roles
Strong communication and presentation abilities
Background with GPUs or distributed computing
Experience with IaC tools (Terraform, Pulumi)
Machine Learning-related certifications
What we offer:
25+ days of vacation, depending on role and progression