Contract-to-Perm ML Engineer (NLP)

**This is a government-contracted project, so you must provide proof of U.S. Citizenship and pass a background check.**

Who We Are:

RAIN is a leader in Voice and Conversational AI. We help businesses navigate voice technology.  We combine strategy, technology, and creativity to drive growth for our clients. We’re guided by the belief that technology is, by definition, an extension of humanity, and that great ideas come from a desire to enhance the lives of real people. 

At RAIN, we want to work with people of different backgrounds and walks of life. We want individuals who can bring diverse perspectives and experiences to our culture and company. We believe that transparency builds trust, so we default to disclosure in our communications. We believe in a safe, welcoming, and inclusive environment.

About the Role:

We are seeking a senior level engineer who can demonstrate their mastery of ML and NLP to automate complex decision models, including leveraging unstructured data and interpreting model results for end users. An ideal candidate can successfully design and implement new machine learning-based approaches using existing frameworks, ensuring they are scalable, accurate, and efficient for our specific use cases.

What You’ll Do:

• Train, validate, and deploy AI models into production systems, ensuring scalability, reliability, and efficiency.
• Generate synthetic data or apply data augmentation techniques to help increase the diversity of the training data and increase the model's generalization ability. 
• Conduct data cleansing, exploration, and feature engineering to sharpen model accuracy and performance.
• Conduct systematic experiments to find the optimal set of hyperparameters for our task.
• Set up automated monitoring systems to maintain model efficacy and performance.
• Further, fine-tune domain-specific or task-specific data to improve its performance by retraining the model on our dataset while leveraging the pre-trained weights from our existing jointBERT model.
• Experiment with modifying the architecture of jointBERT to better suit our specific classification tasks and improve its performance. 
• Use ensemble methods to improve the model performance. 
• Increase the interpretability of the model to help gain insights into its decision-making process and identify areas for improvement. 
• Use different attention mechanisms, such as self-attention, multi-head attention, or hierarchical attention, to improve the model's ability to capture relevant information.

What You’ll Bring:

• Minimum of 6 years of engineering experience. Minimum 3 years of machine learning and NLP experience.
• Expertise in Natural Language Processing (NLP) and Natural Language Understanding (NLU). With demonstrated experience in developing, fine-tuning, and deploying NLP models in production and at scale.
• Practical experience in a wide range of NLP tasks such as classification, named entity recognition, sentiment analysis, machine translation, information retrieval, entity linking, and more. 
• Ability to evaluate pre-existing models and requirements for intent classification from unstructured text.
• Experience with transformer architectures (BERT, jointBERT, and RoBERTa preferred).
• Experience deploying models in enterprise environments focusing on scalability, reliability, security, and efficiency.
• Experience with hyperparameters—tuning models as they grow in volume and complexity.
• Proficient in Python and its associated NLP and ML libraries (e.g., NLTK, SpaCy, Transformers, TensorFlow, PyTorch).
• Experience with data gathering, data quality, system architecture, and coding best practices.
• Familiarity with database technologies (e.g., SQL, NoSQL).
• Ability to generate legitimate synthetic data, including evading incorrect pattern matching and learning mistakes.
• Capable of investigating and applying regularization techniques.
• Familiarity with cloud platforms (AWS, GCP, Azure) and their ML services. 
• Excellent problem-solving, analytical, and communication skills.
• Experience with large language models (including fine-tuning, agents, and RAG). 
• Familiarity with version control (e.g., Git) and CI/CD pipelines for AI/ML-based projects. Containerization (e.g., Docker)  is a plus.
• Experience with enterprise healthcare, virtual care, and/or pharmacy technology is a plus.

Please share GitHub, HuggingFace, or any relevant project links.

Salary will be evaluated commensurate with experience and location.

RAIN is an Equal Opportunity Employer and is committed to fair and equitable hiring practices. All hiring decisions at RAIN are based on strategic business needs, job requirements, and individual qualifications. All candidates are considered without regard to race, color, religion, gender, sexuality, national origin, age, disability, genetics, or any other protected status.

*Note to Recruiters and Placement Agencies: We do not accept unsolicited agency resumes.*