Full Stack Dotnet Developer

Casado; Brasil; Presencial; BRL 240 000 - 360 000; Tempo integral

Resumo da oferta

Casado is seeking a seasoned Full Stack .NET Developer with AI/ML expertise to build cutting-edge AI solutions in life sciences. The role requires 15+ years in IT and end-to-end delivery from requirements to production deployment with minimal AI dependency.

Responsibilities include designing scalable systems, integrating ML models, and leading engineering best practices. Collaboration with cross-functional teams is essential to align AI with business goals.

Qualificações

• Bachelor's or Master’s degree in Computer Science, Engineering, Statistics, or a related field.
• Proven professional experience in software development with strong .NET/C# stack.
• Experience creating and implementing machine learning or AI algorithms.

Responsabilidades

• Design, develop, test, and maintain robust software solutions using .NET Core, C#, and related tech.
• Integrate AI/ML models into apps ensuring performance, scalability, and compliance.
• Own full lifecycle of AI/ML models from data collection to deployment and monitoring.
• Collaborate with data scientists, clinicians, and product managers to translate requirements into technical solutions.

Conhecimentos

C#/.NET

Full-stack dev

AI/ML integration

Cloud platforms

Formação académica

Bachelors in CS

Masters in CS

Ferramentas

Azure

Docker

Kubernetes

TensorFlow

PyTorch

SQL Server

Descrição da oferta de emprego

We are seeking a talented and motivated Full Stack .NET Developer with AI/ML skills to join our clients innovative team, focusing on developing cutting-edge AI/ML solutions within the life sciences domain. The client needs a resource who has at least 15+ years experience in IT. The desire is for a candidate to go from requirement gathering to design, development, test and production deployment with minimal dependency on AI. The more experienced talent is more likely to fit this.

Key Responsibilities

• Design and Development: Design, develop, test, and maintain robust and scalable software solutions using .NET Core, C#, and other relevant technologies (e.g., Python for ML tasks).
• AI/ML Integration: Integrate AI/ML models and algorithms into existing and new software applications, ensuring performance, scalability, and compliance within the healthcare industry.
• Model Lifecycle Management: Own the full lifecycle of AI/ML models, including data collection, preprocessing, model training, validation, deployment, monitoring, and iteration.
• Collaboration: Work closely with cross-functional teams, including data scientists, clinicians, and product managers, to translate business requirements into technical solutions and align AI capabilities with business goals.
• Technical Leadership: Participate in code reviews, foster engineering best practices (e.g., TDD, CI/CD, DevOps), and potentially mentor junior team members.
• Problem Solving: Apply an engineering mindset to analyze complex, large-scale medical data, identify trends, and develop data-driven solutions that accelerate drug discovery or optimize clinical workflows.

Required Qualifications and Skills

• Education: Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related technical field.
• Experience: Proven professional experience in software development, with a strong emphasis on the .NET/C# stack.
• Experience: Working on creating and implementing machine learning or AI algorithms.
• Experience: With full-stack development, including front-end technologies like React or Vue, is a plus.
• Technical Skills: Proficiency in C# and the .NET framework (including .NET Core).
• Programming experience in Python for AI/ML development tasks is often mandatory.
• Familiarity with ML frameworks/libraries (e.g., TensorFlow, PyTorch) and NLP techniques.
• Experience with cloud platforms, particularly Azure, and containerization tools like Docker and Kubernetes.
• Strong experience with SQL Server or other enterprise database environments.
• Knowledge of MLOps practices, CI/CD pipelines, and version control (Git).
• Soft Skills: Excellent problem-solving, analytical, and debugging abilities.
• Soft Skills: Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Soft Skills: A proactive, innovative mindset and passion for continuous learning in AI and healthcare.