AI/ML Engineer
Our Take
Innovate and deliver cutting-edge AI/ML/GenAI solutions for enterprise clients at Spyrosoft.
What you’ll do
- Develop new AI approaches and solutions
- Experiment with cutting-edge AI architectures
- Drive innovation across business use cases
- Deliver scalable AI capabilities
- Contribute to project development
- Collaborate with cross-functional teams
What they’re looking for
- 2+ years Data Science/ML experience
- Proficiency in Python and ML frameworks
- Knowledge of ML, Deep Learning, GenAI
- Understanding of NLP techniques
- Experience with Azure or AWS cloud
- Delivering enterprise AI/ML/GenAI projects
Skills & Focus Areas
- Python
- TensorFlow
- PyTorch
- Pandas
- Scikit-Learn
- Azure
- AWS
- Docker
- Kubernetes
- Git
- Flask
- FastAPI
As posted by Spyrosoft
Project description:
The role includes developing new AI approaches and solutions, experimenting with cutting-edge architectures and driving innovation across business use cases. Additionally, experience in data engineering and cloud platforms will be valuable in delivering scalable and high‑impact AI capabilities.
Main responsibilities:
Proven experience delivering AI / ML / GenAI projects in enterprise environments Demonstrated ability to lead or significantly contribute to project development Strong understanding of the Software Development Life Cycle (SDLC) Experience working in automotive and/or financial services environments is highly preferred Strong communication skills English: mandatory French or German: strong plus
Requirements:
Minimum 2 years of experience in Data Science and Machine Learning.
Knowledge of machine learning, deep learning, and Generative AI (GenAI) techniques.
Proficiency in Python programming language and frameworks like TensorFlow, PyTorch, Pandas or Scikit-Learn.
Understanding of Natural Language Processes (NLP) techniques such as tokenization, string comparison and embeddings.
Experience with cloud platforms such as Azure or AWS.
Good communication and interpersonal skills, with the ability to collaborate effectively with team.
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Nice to have:
Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems.
Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.
Implement monitoring and logging tools to ensure AI model performance and reliability.
Familiar with API building using Flask, FastAPI or similar.