Data Scientist Enterprise AI Solutions

Sakin Tech - Seattle, WA

Full-time

Seattle, WA

About the position

As a Data Scientist in the Enterprise AI Solutions team, you will collaborate with major enterprises to create advanced AI applications. This role involves working with data scientists, engineers, and subject matter experts to implement innovative AI solutions that facilitate data-driven decision-making and enhance digital transformation. You will be responsible for deploying machine learning algorithms and ensuring the scalability and performance of AI solutions.

Responsibilities

• Design and deploy machine learning algorithms for industrial applications such as predictive maintenance, demand forecasting, and process optimization.
• Collaborate with data and subject matter experts from client teams to identify, validate, interpret, and utilize new data elements effectively.
• Drive the adoption and scalability of Generative AI and Deep Learning systems within product offerings.
• Conduct research, analysis, and benchmarking of different AI models.
• Develop and present Points of View (PoV) on various AI models to guide strategic decisions.
• Work with SMEs, Solution Team, and Engineering team to pilot new PoV solutions and scale them out.
• Establish and adopt best practices in MLOps.

Requirements

• MS or PhD in Computer Science, Electrical Engineering, Statistics, or a related field.
• Extensive experience in applied machine learning (regression, classification, supervised, self-supervised, and unsupervised learning).
• Strong foundation in mathematics (linear algebra, calculus, probability, and statistics).
• Proficiency in Python and object-oriented programming languages, such as JavaScript.
• Familiarity with key Python libraries for data manipulation, machine learning, and deep learning (e.g., pandas, scikit-learn, TensorFlow, PyTorch, LangChain).
• Ability to lead projects and work both independently and within cross-functional teams.
• Excellent verbal and written communication skills.
• Proactive, motivated, and eager to make an impact in a dynamic environment.

Nice-to-haves

• Experience with scalable machine learning frameworks (e.g., MapReduce, Spark).
• Expertise in Generative AI, including Large Language Models (LLMs), embedding models, prompt engineering, and fine-tuning.
• Experience with reinforcement learning.
• A portfolio of relevant projects (e.g., GitHub repositories, published papers).