Generative AI Engineer

Summary

Join Analytica as a Generative AI Engineer and contribute to the development and implementation of cutting-edge AI and LLM models for enterprise software applications within the federal sector. You will leverage your expertise in software engineering, AI fine-tuning, statistical programming, modeling, NLP, and data mining to create impactful solutions for public sector challenges. Analytica is a rapidly growing company recognized for its work with U.S. government clients across various missions. We offer a competitive compensation package that includes bonuses, employer-paid healthcare, training funds, and a 401k match. This role requires a strong background in NLP, experience with various AI/ML models and techniques, and proficiency in Python and related technologies. The ideal candidate will have a Master's or PhD in a relevant field and 5-10 years of experience. You will be responsible for data preprocessing, feature engineering, model selection and validation, and presenting results to leadership.

Requirements

• Master's degree or PhD is highly preferred in Statistics, Mathematics, Computer Science, or similar
• 5-10 years of relevant professional experience is a similar role is required
• High degree of experience utilizing Python to support NLP use cases such as Document Summarization, Named Entity Recognition, Sentiment Analysis, and/or Topic Modeling
• Experience in software engineering integrating APIs and micro-services working in a cloud environment and hands on experience with AWS is required
• Some competency with computer vision is required
• Experience with multi-modal GenAI/LLMs and prompt engineering techniques using leading models such as Claude, Llama, etc
• Familiarity with Databricks is required
• Must be a US citizen
• Must be able to obtain and maintain a Public trust security clearance

Responsibilities

• Pre-processing - Demonstrate the skills and experience to collect, clean, and prepare data sets for input into a computational model using technologies such as Python. Strong candidates will explain various methods you have applied using common pre-processing functions such as stop word removal, stemming, lemmatization, and tokenization
• Feature Engineering and Attribute Evaluation - Candidate must demonstrate experience with NLP feature engineering methods such as TF-IDF, word2vec, GloVe, and FastText identifying the key determinants for modeling that exist in the business process and within existing data sets as well as selecting evaluation protocols (model techniques)
• Modeling - Candidates will have practiced skills and experience selecting modeling techniques to fit the business problem. Examples will include techniques such as machine learning (ML) supervised and unsupervised learning, regression, neural networks and deep learning, natural language processing, etc
• Validation - Strong candidates will describe their experience with investigating, reporting, and justifying model results
• Visualization- Experience in presenting the results of their modeling activities, depicting the insights realized, and explaining the relevance of their results to the organization’s business challenges

Preferred Qualifications

• At least four years of experience developing scalable, production-ready NLP solutions using sci-kit learn, Keras, TensorFlow, PyTorch, Spark NLP is preferred
• Experience with open source NLP packages such as Gensim, SpaCy, or NLTK
• Experience leveraging transformer architecture to develop NLP models and experience with BERT, GPT-J, RoBERTa, T5 or other transformers
• Experience presenting findings to executive leadership or mid-level management

Benefits

• Competitive compensation with opportunities for bonuses
• Employer-paid health care
• Training and development funds
• 401k match