Data Scientist

ImpetusIT; Boston (MA); On-site; USD 60,000 - 70,000; Full time

Job summary

ImpetusIT is seeking a Data Scientist for a pharma client in the Boston area. The role offers an annual salary in the $60k–$70k range and requires hands-on work with cutting-edge AI technologies, including large language models and NLP.

The ideal candidate will design, train, and deploy ML/DL models, collaborate with cross-functional teams, and contribute to real-world applications in a regulated pharma environment.

Qualifications

• Experience designing, training, and fine-tuning large language models.
• Strong background in ML/DL and NLP concepts.
• Hands-on experience with LLMs (GPT, Llama, PaLM or similar).

Responsibilities

• Design, train, and fine-tune Large Language Models (LLMs) for various applications.
• Deploy, monitor, and optimize AI models in cloud environments.
• Collaborate with cross-functional teams to integrate AI into real-world applications.
• Strong background in Machine Learning, Deep Learning, and NLP.
• Hands-on experience with LLMs (GPT, Llama, PaLM, or similar).
• Knowledge of transformer architectures, attention mechanisms, and reinforcement learning.
• Experience with fine-tuning and optimizing foundation models.
• Experience with AI model deployment and optimization techniques.

Skills

LLMs

Machine Learning

Deep Learning

NLP

Transformer architectures

Reinforcement learning

Model deployment

Job description

One of our staffing partners is helping a pharma client hire a Data Scientist

Salary offered $60-70k per year

Direct applicants only no c2c or company candidates due to low margins. The staffing company or client will reach directly to the applicants.

Responsibilities:

• Design, train, and fine-tune Large Language Models (LLMs) for various applications
• Deploy, monitor, and optimize AI models in cloud environments
• Collaborate with cross-functional teams to integrate AI into real-world applications
• Strong background in Machine Learning, Deep Learning, and NLP
• Hands-on experience with LLMs (GPT, Llama, PaLM, or similar)
• Knowledge of transformer architectures, attention mechanisms, and reinforcement learning
• Experience with fine-tuning and optimizing foundation models
• Experience with AI model deployment and optimization techniques