Senior Machine Learning Engineer (NLP/LLM Focus)

Job Type

Full-time

About the role

We build and deploy AI-driven solutions that leverage cutting-edge Natural Language Processing (NLP) and Large Language Models (LLMs) to solve complex business problems in real-world environments. As a Senior Machine Learning Engineer specializing in NLP and LLM-powered models and microservices, you'll play a key role in shaping and delivering ML-powered products that transform how we process and extract insights from unstructured data.

Responsibilities

• Lead the design, development, and deployment of NLP and LLM-powered models that drive key products and business functions.
• Turn cutting-edge models into production-ready, scalable solutions, ensuring seamless integration into our applications.
• Build APIs and pipelines that power AI-driven insights from a variety of data sources like call transcriptions and enable our products to understand and process natural language data, including text classification, conversational AI, and document analysis.
• Collaborate with product teams, engineers, and other stakeholders to drive the vision and execution of ML-powered solutions.
• Ensure MLOps best practices are followed, with a focus on model monitoring, versioning, and retraining workflows.
• Serve as a technical mentor through code reviews, pair programming, and guidance on best practices.

Requirements

• Relentless passion for learning, growth, and excellence in the field of machine learning.
• 5+ years of experience in machine learning engineering with a focus on NLP and LLM technologies (e.g., BERT, GPT, or similar transformer models).
• Proven experience in building and deploying large-scale NLP models for real-world applications.
• Expertise in turning research-based models into scalable, production-level solutions.
• Strong programming skills in Python, with deep familiarity in libraries like TensorFlow, PyTorch, or Hugging Face.
• Experience with cloud-based infrastructures (AWS, Azure, GCP) and tools like Kubernetes, Docker, and MLflow.
• A team-oriented mindset, with a passion for collaborating and mentoring others.

Preferred Skills

• Hands-on experience with data engineering tasks such as data pipelines, ETL processes, and working with big data technologies like Spark.
• Familiarity with MLOps tools and practices, including continuous integration/deployment pipelines for machine learning applications.
• Expertise in automation of model retraining and ensuring long-term scalability and performance of deployed models.
• Experience with the automotive sales industry, voice recognition, or call center technologies.

Benefits

• Competitive salary ranging from based on experience.
• Medical and dental insurance options.
• Company provided Long Term Disability and Life Insurance.
• 401k with company match to help secure your financial future.
• A monthly wellness allowance, reading stipend, and other perks to ensure a healthy work-life balance.
• Clear opportunities for career growth with mentorship from senior leaders.
• An exciting, collaborative work environment with regular team-building activities, and company events.