As an ML Engineer, you will play a key role in advancing machine learning capabilities with a strong emphasis on Generative AI. Your work will involve designing, training, and optimizing models using leading frameworks and tools, while aligning technical solutions with real-world business needs.
Key Responsibilities
- Develop and fine-tune machine learning models with a focus on NLP and generative systems
- Implement Generative AI applications using tools such as LangChain, AutoGen, and CrewAI
- Explore and integrate emerging AI techniques, algorithms, and research advancements
- Collaborate with senior engineers and stakeholders within an Agile workflow to deliver scalable solutions
- Document models, experiments, and outcomes thoroughly to support transparency and reuse
- Stay current with advancements in AI and apply relevant innovations to active projects
Required Skills
- Strong proficiency in Python and experience with ML libraries including PyTorch, TensorFlow, or Sklearn
- Hands-on experience with NLP tools such as Hugging Face, Spark NLP, or NLTK
- Familiarity with Generative AI frameworks like LangChain, AutoGen, or CrewAI
- Experience using GitHub and CI/CD pipelines for model deployment
Preferred Qualifications
- Knowledge of MLOps platforms such as MLflow or AutoML
- Cloud experience, particularly on Azure
- Background working in Agile development environments
Work Environment
This role operates in a hybrid setup, offering flexibility in where and how you work. The environment supports continuous learning and professional growth through resources like LinkedIn Learning and an Employee Assistance Program. Volunteer time off is available to support community engagement.
Our Values
We are committed to diversity, equity, and inclusion across all aspects of our work. Our AI practices emphasize fairness, transparency, and human oversight. We value innovation driven by diverse perspectives and maintain a strong dedication to the communities we serve.
