Senior Data Scientist

Overview

Remote
$50 - $55
Contract - W2
Contract - 6 Month(s)

Skills

Python
Semantic Search
Technical Writing
Version Control
Performance Tuning
Prompt Engineering
Microsoft Azure
Machine Learning (ML)
Jenkins
GitLab
GitHub
Git
DevOps
Continuous Delivery
Continuous Integration
Cloud Computing
Code Review
API
Algorithms
Amazon Web Services
Artificial Intelligence
BERT
Writing
Use Cases

Job Details

Note : for this following role , we are looking for only those applicants who are willing to Join and work on our company's W2 basis , Unfortunately we cannot accept those consultants who are looking for Contract or C2c based roles , Third party companies or Employers please do not apply.

Job Title : Senior Data Scientist
Location : Remote
Duration: 6 Months+

Master's or PhD Preferred!
- 5-10+ years of experience in AI and machine learning, model building and strong coding skills in python
- 2+ years of working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc. UTILIZING RAG!
- Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.
- Experience with conversational search / semantic search, reinforcement learning, prompt engineering, hallucination mitigation
- DevOps repos Debugging, building APIs and managing the algorithm flow across multiple workstreams in one repo
- Senior level experience deploying models in the Cloud (AWS) or Azure as secondary.

- FANG Experience (Facebook, Amazon, Netflix, Google, or even Microsoft)
Secondary Skills - Nice to Haves
o Python
o Machine learning
o cloud computing
Job Description:

The Senior Data Scientist will focus on search and be dedicated to the creation of next-generation AI and Machine Learning techniques and strategies for LexisNexis in their global expansion. This candidate will assist with deploying ethical, powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model for each individual legal use case. This approach includes working with large language models like Anthropic s Claude 2, hosted on Amazon Bedrock from Amazon Web Services (AWS), and OpenAI s GPT-4 and ChatGPT, hosted on Microsoft Azure.

Core Technical Skills
Python Proficiency:

Expert level of Python, with experience in writing efficient, clean, and modular code.
Ability to debug and test new code thoroughly.
RAG Systems:

Experience and deep understanding of Retrieval-Augmented Generation (RAG), including concepts like embedding-based search, document retrieval, and combining retrieved information with LLMs.
Hands-on experience with advanced RAG platform development and maintenance.
Familiarity with knowledge base creation, indexing, and retrieval pipelines.
Knowledge of AI Architectures:

Understanding of the end-to-end architecture of generative AI systems, including pre-processing, retrieval, ranking, and post-processing steps.
Prompt Engineering:

Expertise in crafting effective prompts for LLMs tailored to specific tasks.
Experience with techniques like zero-shot, few-shot prompting, prompt tuning, and chain of thought.
Content Generation:

Understanding of generative AI applications in content creation, including best practices for producing accurate, coherent, and domain-specific outputs.
Ability to fine-tune components for custom use cases.
Debugging and Performance Tuning:

Skills in profiling and optimizing LLM responses for latency and accuracy.
Experience diagnosing issues in complex multi-component systems.
Monorepo and Collaboration Skills
Working in Monorepo Environments:

Experience managing and contributing to large, centralized codebases (monorepos).
Understanding of version control workflows suited for monorepos (e.g., Git-based branching strategies).
Collaboration Tools and Practices:

Proficient with CI/CD pipelines and tools like Jenkins, GitHub Actions, or GitLab CI.
Ability to work collaboratively with cross-functional teams in Agile settings.
Proficiency with code review practices and tools.
AI and NLP Knowledge
NLP Expertise:

Solid understanding of transformers, embeddings, and attention mechanisms.
Familiarity with techniques for handling domain-specific language models.
Complementary Skills
Documentation and Communication:

Ability to write clear technical documentation for processes, workflows, and API usage.
Strong communication skills for conveying technical insights to stakeholders.
Preferred Experience
Previous experience working in legal tech or domain-specific generative AI use cases.
Hands-on experience with deploying AI models in production at scale.
Familiarity with multilingual generative AI and fine-tuning for specific languages like French.
Senior group no micromanagement, no hand holding, no recent college grads
This is an extremely high visibility group. Lexis + AI is the company's flagship product and expanding globally to various locations
Extremely competitive compensation

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