Machine Learning Engineer (Large Language Models)

Key Skills

Aartificial intelligence, Analytical and Problem solving, Azure, Computer Vision (CV), Deep Learning, Large Language Models - LLMs, Machine learning techniques, Natural Language Processing (NLP), Python Programming, PyTorch, Reinforcement Learning, TensorFlow

Job Description

At BASF, we create chemistry through the power of connected minds. By balancing economic success with environmental protection and social responsibility, we are building a more sustainable future through chemistry. As the world’s leading chemical company, we help our customers in nearly every industry meet the current and future needs of society through science and innovation.

We provide a fulfilling work environment with a strong emphasis on the physical and psychological safety of our employees and the communities we operate in. We are always working to form the best team with an emphasis on diversity, equity, and inclusion and through lifelong learning and development.

At BASF, we constantly strive to become an even better workplace. As a result of our commitment to our employees, BASF has earned various awards, including being recognized by Mediacorp as a Top Employer in Canada and the GTA in 2023, and for many consecutive years prior. We are also thrilled that, for the first time ever in 2023, we have been further recognized by Mediacorp as one of Canada’s Top Employers for Diversity, as well as for Young People.

We invite you to join our best team on our journey to create solutions for a sustainable future!

• Machine Learning Engineer (Large Language Models)
• Working Model: Hybrid
• Location: Mississauga, ON

Where the Chemistry Happens…

BASF is a leader in the chemical industry, driving innovation and sustainability through cutting-edge technology. We are currently seeking an experienced Machine Learning Engineer with a strong background in Large Language Models to join our growing team of AI Enthusiasts. In this role, you will have the opportunity to leverage cutting-edge AI technologies to reshape the way we approach chemical research, development and operations. If you are passionate about Large Language Models, have a strong background in ML Engineering and enjoy working on cutting-edge topics, we would love to hear from you!

Formula for Success: You Will…

• Design, develop, and deploy AI-based solutions using Large Language Models to address specific challenging use cases in various domains.
• Collaborate with domain experts and cross-functional teams to understand domain-specific problems and identify opportunities for AI-driven innovation.
• Integrate AI solutions into our existing workflows and platforms.
• Continuously improve and optimize AI models to enhance their accuracy, efficiency, and scalability.
• Share your knowledge and expertise with colleagues and promote a culture of AI-driven innovation within the organization.

Qualifications

Ingredients for Success: What We Look for in You…

• Master's degree or PhD in Computer Science, Data Science, Artificial Intelligence, or a related field.
• Strong experience in working with deep learning architectures like transformers and related models (such as GPT-3 or similar models).
• Excellent programming skills in Python, and experience with machine learning frameworks such as TensorFlow or PyTorch.
• Experience with cloud platforms (ideally Microsoft Azure), containerization technologies and with deploying and managing AI solutions in a cloud environment.
• Excellent problem-solving, critical thinking, and communication skills.
• Continuous learning to keep up with the rapid technological developments in the field of AI.

Nice-to-have:

• Proven track record of successful AI-driven projects, preferably in an industrial or research setting.
• Experience in prompt engineering and fine-tuning large language models for specific applications, experience with frameworks like LangChain or LlamaIndex.
• Experience with other AI technologies, such as natural language processing, reinforcement learning or computer vision.
• Knowledge of data engineering and preprocessing, including handling large datasets and ensuring data quality.
• Familiarity with AI ethics and responsible AI practices.