Lead ML Engineer

SwissPine Tech is seeking a highly experienced Machine Learning Engineer with a track record of developing complex, high-impact software products. Someone who can thrive at the intersection of cutting-edge technology and real-world value creation. A hands-on expert to architect, build, and operationalize the AI-driven systems that deliver tangible business value.

As a Senior ML Engineer, you will be a pivotal part of our strategic initiative to develop data-driven software. This role combines deep technical execution with cross-functional collaboration, bridging the gap between data science, software engineering, and our data platform. If you're ready to shape strategy, architect scalable systems, and be part of advanced AI initiatives from concept to production, this is your opportunity to develop, influence, and deliver at scale. You'll be stepping into a company that prioritizes technical excellence, trust, and innovation, where you won't just be applying AI—you'll be influencing where it goes next.

Key Responsibilities

• Translate & Strategize: Act as the bridge between data science and strategy, translating complex technical solutions into measurable business outcomes.
• Integrate & Innovate: Partner closely with key stakeholders to embed AI into the core of our products and services.
• Own MLOps: Take full responsibility for our MLOps infrastructure, enabling the team to efficiently develop, test, deploy, monitor, and retrain AI models.
• Deliver via APIs: Design, develop, and maintain robust and scalable APIs that allow other internal and external applications to utilize our AI solutions.
• Build the Foundation: Contribute actively to our data platform, from data collection and processing to surfacing valuable information that enables the development of AI models.
• Stay Ahead of the Curve: Champion the adoption of emerging technologies, methodologies, and best practices in AI, data science, and optimization.
• Mentor & Lead: Lead by example by mentoring other data scientists and data engineers, helping to foster a collaborative, high-performance culture.

Must-Have Skills:

• Education & Experience: Master's (or higher) in CS/EE/Math/Stats or equivalent experience; 5+ years in ML/Data/Platform roles shipping AI systems to production (not just notebooks).
• Python engineering: Strong software fundamentals (testing with pytest, packaging, typing), ML frameworks (e.g., PyTorch or TensorFlow), and data stacks (Pandas/NumPy).
• MLOps & Cloud: CI/CD for ML (GitHub Actions/GitLab/Azure DevOps), experiment tracking & model registry (e.g., MLflow/W&B), containerization (Docker) and orchestration (Kubernetes), with hands-on experience on AWS/Azure/GCP.A Master's degree or higher in Computer Science, Data Science, Engineering, or a related quantitative field.
• 5+ years of relevant experience in machine learning, data science, and/or data engineering with a proven track record of developing services in the cloud.
• Demonstrated experience delivering end-to-end AI systems into production, moving beyond theoretical models in notebooks to solve complex, real-world problems.
• A solid grasp of DevOps and MLOps best practices, including CI/CD for models, automated monitoring, retraining pipelines, and version control.
• Expert-level Python development skills with experience in building production-grade applications.
• Strong background in API development and integration.

Nice-to-Have Experience:

• Experience with a major cloud platform (Azure, AWS, or GCP).
• Familiarity with container technologies like Docker and orchestration tools like Kubernetes.
• Previous experience in a consulting or client-facing role, translating business needs into technical solutions.
• A passion for collaborative problem-solving and knowledge-sharing within a team.