Key skills
Machine learningArtificial intelligencePythonLLM APIsAgentic frameworksPrompt engineeringPyTorchScikit-learnSoftware engineering fundamentalsVersion controlTestingCI/CDHealthcare dataElectronic health recordsAIMachine LearningMLLLMLangChainAgenticscikit-learnVersion ControlPrototyping
About this role
Akkodis is seeking a Machine Learning Engineer for a contract role. In this position, you will design, build, and ship AI agents and automation solutions while collaborating with various stakeholders to enhance engineering workflows and customer-facing operations.
Responsibilities:
- Develop and implement AI Agents and automation that accelerates internal engineering workflows and customer facing delivery processes, owning the full lifecycle from problem discovery, through prototyping, evaluation, hardening, and production deployment
- Partner with software engineers to integrate AI into the company's existing software infrastructure, supporting seamless functionality and performance
- Work directly with product managers, implementation consultants, engineers, and business operations teams to identify pain points, scope solutions, and iterate toward measurable outcomes
- Stay current with advancements in LLMs, agentic frameworks, machine learning, and healthcare technology, and apply new knowledge to contribute ideas for innovation within the team
- Optimize AI systems for accuracy, latency, cost, and safety, with particular attention to human-in-the-loop design and guardrails appropriate for healthcare
- Maintain clear documentation of model development processes, methodologies, and results to ensure transparency and reproducibility
Requirements:
- Master's degree in computer science, Machine Learning, Data Science, or a related field. A Bachelor's degree with relevant experience will also be considered
- 2–4 years of experience building and deploying ML or AI systems in production
- Experience working directly with non-technical stakeholders or in embedded/consulting-style engineering roles is a strong plus
- Strong proficiency in Python
- Experience with LLM APIs, agentic frameworks (LangChain, Strands, etc.), and prompt engineering alongside traditional ML frameworks (PyTorch, scikit-learn, etc.)
- Solid software engineering fundamentals — version control, testing, CI/CD, and comfort operating across the full development lifecycle
- Interest in or familiarity with healthcare data, clinical workflows, and regulatory requirements
- Strong problem-solving skills and the ability to work with complex datasets to derive actionable insights
- Experience working with electronic health records (EHR) or other healthcare datasets is a plus but not required