Apprentice Generative Ai Engineer Jobs in Boston, MA

Must have GenAI, Machine Learning, LLM, RAG, Python and Data Science.

Must have someone with BioTech or Pharma.

Must be onsite day 1.

Title: Enterprise Generative AI Engineer

# Open (if applicable): 1

Max Submittals (if applicable): N/A

Basic Company Info: BioTech

Location: Waltham, MA

Location Details: Free parking - Café Onsite

Why Open: They are looking for someone to build out their AI environment to build specific workflows that cannot be addressed by "off the shelf" AI systems such as copilot and ChatGPT.

Start: ASAP

Duration: 6 Months w/ Extensions

Important Skills

Technical - Machine Learning Engineering, Data Science, Python, RAG (retrieval augmented generation), LLM (large language models)

Soft - White Glove communication skills (working with scientists), technical knowledge translation, cross-functional collaboration

Interview Process: Two Step Interview Process

1st Step: Hour long virtual interview (30 min with Director of IT - 30 min with Director of Research,)

2nd Step: 2 Hour Onsite interview

Background Check: Standard Background Test

What the environment / Sell:

We are intentional about supporting and growing our culture where people can invent, discover, and have fun along the way. Very tight knit company of about 120 employees. Subsidiary of Otsuka Pharmaceutical's. They have free parking, a cafeteria, a bistro, and a gym all onsite.

Hours / Shift (if applicable): Hybrid: 3 days onsite.40 Hours/ Week - 9am-5pm

Notes: Business Casual Dress Code

Logos: Yes

Job Title: Senior Enterprise Generative AI Engineer - LLM Assistants and Copilots

Location: Waltham, MA / Hybrid

Level: Mid/Senior

They currently use Copilot and ChatGPT as their "off the shelf" AI tools but are looking for someone that can build specific proprietary AI workflows to help address needs that their off the shelf tools cannot. They will be using the Azure AI Studio to build out these workflows which uses Python as the programming language. They are looking for someone that is very forward thinking and can build out an AI environment to support the specific needs of Scientists and other internal employees.

They need to have previous knowledge and experience with RAG (retrieval augmented generation) and LLM (large language models). They are going to prefer candidates with data engineering and cloud solutions experience. Please reach out with any questions!

Job Description:

Seeking a talented and visionary Enterprise GenAI Engineer to lead our organization's GenAI initiatives for productivity and business use cases. In this role, you will play a crucial role in identifying, developing, deploying, and managing enterprise Generative AI/LLM solutions in the form of custom assistants, chatbots and copilots to address business needs. You will develop applications by tailoring use of LLM capabilities through prompt engineering, RAG (retrieval augmented generation) and other AI/ML/NLP techniques.

This role involves collaborating with team members, including from research (biomedical), legal, clinical, HR, and finance departments, to create scalable, efficient, and accessible AI/LLM applications. This role involves leveraging cloud-based AI resources that support LLM-based application development, such as Azure AI studio, AWS Sagemaker, OpenAI and Google Vertex AI. This role involves leading and pioneering new capabilities of LLMs to advance core workstreams involving data analysis, content generation, summarization and problem solving. Your work will directly contribute to making GenAI application development more intuitive and accessible to several teams.

Responsibilities:

• Design, develop, and deploy private end-to-end AI chatbots and solutions leveraging GenAI / LLM models and RAG pipelines through cloud AI environments, such as Microsoft Azure AI (Copilot) Studio, OpenAI GPT, AWS SageMaker and other platforms.
• Work closely with senior director of enterprise systems and employees to identify and define business use cases for tailored Gen AI / Copilot solutions, involving RAG, prompt engineering and document/content specification. Architect, implement and support innovative solutions to meet the business need objectives.
• Ensure the performance, quality, and responsiveness of applications (chatbots/copilots).
• Establish design principles, architecture standards and best practices in alignment with IT strategy. Uphold high standards for cloud security and data privacy.
• Collaborate with cross-functional teams to identify opportunities for LLMs to enhance productivity and effectiveness to solve business needs. Propose and implement end-to-end solutions.
• Implement feedback mechanisms to address architectural challenges and enhance utility of custom application builds.
• Stay abreast of emerging trends and advancements in GenAI technologies and support solutions for enterprise to improve offerings and tailored solutions for business needs.

Qualifications:

• Bachelor's or master's degree in computer science, machine learning, data science, software engineering, or a related field.
• 5+ years experience in data science, AI/machine learning, enterprise software development, or related roles to create, implement and support advanced data science (AI/ML) and IT solutions for enterprise needs.
• Proven experience in AI and machine learning, including familiarity with LLMs, RAG (retrieval augmented generation) pipelines, and NLP (natural language processing) techniques.
• Experience with RAG (retrieval augmented generation), neural networks, Natural Language Processing (NLP), knowledge graphs (KPs) and other AI/ML approaches.
  • Experience with API / API Management.
• Preference for programming skills in Python and associated ML packages.
• Knowledge of cloud computing concepts and experience with enterprise cloud management systems, preferably Microsoft Azure.
• Excellent problem-solving skills and the ability to work in a fast-paced environment.
• Strong communication and teamwork skills.
• Prior experience in biotech/healthcare enterprise data science/IT needs is preferred.