GenAI Data Scientist

MM Management Consultant; Teletrabalho; BRL 250.000 - 350.000; Tempo integral

Resumo da oferta

A leading consultancy firm seeks a Senior Data Scientist specializing in Generative AI. This remote position requires a minimum of 8 years of experience, including expertise in Python, NLP, and machine learning. The candidate will architect frameworks for GenAI products, mentor junior teams, and collaborate with product managers to deliver impactful AI solutions. Ideal applicants should hold an advanced degree in a technical discipline and have substantial experience with LLMs and cloud platforms like AWS.

Qualificações

• Minimum of 8 years of total experience in relevant fields.
• Experience in developing machine learning models impacting business value.
• Knowledge of large language model architectures.

Responsabilidades

• Architect frameworks for GenAI products and optimize model performance.
• Collaborate with product management and engineering leads.
• Mentor junior data scientists on GenAI methods.
• Evaluate new data science technologies for business value.

Conhecimentos

Python

Natural Language Processing (NLP)

Machine Learning

Cloud Computing (AWS)

Deep Learning (PyTorch/TensorFlow)

Data Analysis

Model Optimization

Formação académica

Advanced degree in mathematics, physics, computer science, engineering, statistics

Ferramentas

Langchain

BERT

GPT-3

Descrição da oferta de emprego

GenAI Data Scientist

Exp- Minimum 8 years

• 100% remote/Long Term Contract/EST hrs.

Job Role

As a Senior Data Scientist, you will translate the needs of our cross-functional stakeholders into user-facing applications that leverage NLP techniques and large language models (LLMs). As a Sr. Data Scientist on our GenAI applications team, you will work on products like conversational search interfaces, chatbots, text summarizers, recommender engines, and more based on the needs of the constituents. You will partner with Product Managers, Machine Learning Engineers, Cloud Platform Engineers, and cross-functional partners to develop production-grade algorithms.

You will contribute to the creation, delivery, and production of specific data science, machine learning and AI products for internal stakeholders; directly mentor other data professionals, data analysts, and machine learning engineers. In conjunction with the key partners, you will make technical decisions on data, technology, and ways of working

Duties and Responsibilities

• Architect the overall framework and infrastructure for GenAI products like search interfaces, bots, summarizers, etc. Develop and implement techniques to optimize model performance to meet specific product goals
• Collaborate closely with product management and engineering leads to align on technical roadmap. Guide engineering teams to effectively leverage LLM capabilities in product implementation.
• Identify trends and opportunities to drive innovation, both in what we do and how we do it; evaluate new data science, machine learning, and AI technologies and tools that can boost team performance, innovation and business value. Proactively analyze latest developments in large language models to deeply understand model capabilities, limitations, and best practices. Develop techniques to continually improve language understanding and model training
• Mentor and develop junior data scientists in state-of-the-art GenAI methods
• Set technical vision and lead initiatives to accelerate product impact through cutting-edge LLM innovations
• Complete other responsibilities as assigned.

Required Skills and Qualifications

• Total Exp: 8 to 10yrs+
• Advanced degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline.
• Minimum of three years’ experience in developing machine learning models with a track record of creating meaningful business impact and working with multiple stakeholders.
• Minimum of five years’ experience with Python.
• Minimum of 3 years of experience building production NLP and deep learning models using PyTorch/Tensorflow, along with using large language model architectures (BERT, GPT-3 etc.)
• Experience building advanced workflows such as retrieval augmented generation, model chaining, dynamic prompting, PEFT/SFT, etc. using Langchain and similar tools
• Experience establishing model guardrails and developing bias detection and mitigation techniques for AI applications
• Proficiency with various prompting techniques, with a clear understanding of tradeoffs between prompting and finetuning
• Experience with finetuning embedding models and tuning vector databases to improve performance of semantic search and retrieval systems
• Deep understanding of underlying fundamentals such as Transformers, Self-Attention mechanisms that form the theoretical foundation of LLMs
• Experience with cloud computing platforms and tools (AWS).
• Experience operationalizing end-to-end machine learning applications.