- Implement, fine-tune, and manage AI models within Databricks and Azure platforms.
- Develop and refine advanced AI and machine learning models, with a focus on natural language processing, using RAG and LangChain models.
- Develop robust, scalable data processing and machine learning pipelines across Databricks, AWS, and Azure.
- Experience in model performance tuning to take advantage of parallel process and hardware capabilities.
- Lead the seamless integration of fine-tuned AI/ML models into business systems and workflows, ensuring effective deployment and scalability.
- Collaborate with software development teams to embed advanced AI capabilities into applications and products.
- Conduct complex data analysis, preprocessing, and feature engineering to optimize model performance.
- Stay abreast of the latest developments in AI, machine learning, RAG, LangChain, and cloud technologies, applying new techniques and approaches to enhance business solutions.
- Effectively communicate complex technical concepts and solutions effectively to stakeholders and team members.
- Provide guidance and mentorship to fellow data scientists and data engineers, fostering professional growth and development.
- Bachelor's or Master's degree in Computer Science, Data Science, AI, or related fields;
- 5+ years of experience in data science with a strong focus on AI and machine learning implementations or PhD in data science with relevant experience. Pertinent experience at the professional level may be substituted for the education requirement on a year-for-year basis for those with a PhD.
- Extensive experience with cloud platforms: Databricks, AWS (e.g., SageMaker, Lambda, EC2), and Azure (e.g., Azure ML, Azure Functions).
- Proven track record in implementing and fine-tuning AI solutions, particularly using RAG and LangChain models.
- Deep understanding of machine learning algorithms, data structures, and software development principles.
- Excellent problem-solving, analytical, leadership, and communication skills.
- PhD degree preferred.
- Expertise in Python, SQL, and familiarity with R and other programming languages.
- Demonstrated experience with conversational AI and chatbot frameworks.
- Publications or presentations in relevant AI/ML communities or conferences.
- Active contributions to open-source projects or participation in the AI/ML technical community.
- Certifications in Databricks, AWS, Azure, or relevant AI/ML technologies.
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Data Scientist - Houston, United States - Motiva
![Motiva background](https://contents.bebee.com/companies/us/motiva/background-AOEMb.png)
Description
Headquartered in Houston, Texas, Motiva refines, distributes, and markets petroleum products throughout the Americas. The company's Port Arthur Manufacturing Complex in Port Arthur, TX, is comprised of North America's largest refinery with a total throughput of 720,000 barrels per day, the world's second largest lubricants plant, and an integrated chemical plant. Under exclusive long-term brand licenses with Shell and Phillips 66 (for the 76 brand), Motiva's commercial operations supply more than 12 billion gallons of fuel to customers annually. Motiva is wholly owned by Aramco, one of the world's largest integrated energy and chemicals companies.Position Overview:
As a Data Scientist at Motiva, your primary responsibility will be to design and execute advanced AI and machine learning solutions. Your pivotal role will involve harnessing platforms such as Databricks, AWS, and Azure to craft scalable, efficient, and inventive AI-driven applications. Specifically, you'll focus on refining models and leveraging methodologies like RAG and LangChain.
Responsibilities:
Basic Qualifications:
Applicants for regular U.S. positions must be authorized to work in the United States for Motiva Enterprises LLC without the need for sponsorship of an immigration authorization or visa (for example, TN, H-1B, or other employment-based immigration authorization or visa).
Motiva participates in E-Verify.
All qualified applicants will receive consideration for employment without regard to race, color, sex, national origin, age, religion, disability, sexual orientation, gender identity, protected veteran status, citizenship, genetic information, or other protected status under federal, state, or local laws.