LLM Scientist/Engineer INTL Nearshore Mexico/Brazil

What we need:
Candidates with Gen AI hands on project experience at least 1-2 projects must be on the PLATFORM side

Candidates are falling short on fundamental concepts and experience building genAI platforms
We need strong hands-on experience building production grade applications.
LLMOps
RAG/Langchain
GenAI

The project scope has increased from building MVP to enterprise grade platform and the LLMOps Scientists will be responsible for scaling, new feature additions, enhancements, and onboarding of models. The addition of the AI Project Manager is a net new add to bring aboard more AI specific knowledge to the services being currently provided. The LLMOps Engineering service and an additional one (1) Senior Technical Program Manager is being added in now that we have released classical ML monitoring platform (Phase 1), for Phase 2 the team is extending it to LLM, so our service will need LLMOps expertise and additional Technical Program Management to complete this work.

United Airlines is seeking a talented and experienced LLMOPS Data Scientist to join our growing team. As a member of our Data Science group, you will play a crucial role in developing and deploying state-of-the-art language models and ensuring their responsible and efficient operation. If youre passionate about natural language processing (NLP), machine learning (ML), and operationalizing AI, this role is for you!

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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1. Model Architecture and Understanding:
o Demonstrate a deep understanding of transformer architectures, including LLMs (Language Models), and their applications in NLP tasks.
o Familiarity with RNNs (Recurrent Neural Networks) and LSTMs (Long Short-Term Memory networks).
2. Responsible AI and Performance Metrics:
o Experience working with Responsible AI practices, including validators for toxicity, profanity, bias, and prompt injection.
o Proficiency in performance metrics such as BLEU, ROUGE, MAUVE, and Bleurt.
o Familiarity with LLM-based scoring methods.
3. Model Fine-Tuning and Open Source Libraries:
o Hands-on experience with fine-tuning LLMs using techniques like LORA, QLORA, and RLHF (Reinforcement Learning from Human Feedback).
o Proficiency in using open-source libraries such as Hugging Faces datasets, ragas, textstat, torch, and Huggingface.
4. RAG Use Cases and Anthropic Collaboration:
o Collaborate with the Anthropic team and work on RAG (Retrieval-Augmented Generation) use cases.
o Apply LLMs to solve real-world problems and enhance user experiences.
5. AWS and Platform Experience:
o Strong working knowledge of AWS (Amazon Web Services) for deploying and scaling ML models.
o Hands-on experience with cloud-based infrastructure and services.
6. MLOPS and Engineering Pipelines:
o Design, implement, and maintain ML engineering pipelines.
o Ensure smooth model deployment, monitoring, and maintenance.
Qualifications:
Experience:
o Minimum 3 years of hands-on experience in LLMOPS/MLOPS roles.
o Demonstrated expertise in TensorFlow, PyTorch, Langchain, Scikit-learn (Sklearn), Argo, Docker, Spark, Postgres, and Redis.
o Full lifecycle experience with classical ML models and LLMs, including EDA (Exploratory Data Analysis), training, inference, monitoring, and fine-tuning.
o Code-heavy experience with designing and implementing ML pipelines.

Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.