What are the responsibilities and job description for the Senior Machine Learning Engineer (NLP/LLM Focus) position at CALL BOX?
Description
At Call Box, we believe in fostering growth—both personal and professional. We hire smart, ambitious individuals who are passionate about technology and empower them to push the boundaries of what's possible. 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. You'll focus on deploying scalable, high-impact solutions, with an emphasis on productization rather than research. If you're passionate about using advanced NLP techniques to solve real-world problems and have a knack for deploying and maintaining models at scale, this is the role for you.
We use a wide range of tools including Python, TensorFlow, PyTorch, Hugging Face, SQL, Kubernetes, Docker, Azure, and AWS. Candidates with experience in data engineering or MLOps (e.g., MLflow, CDK/terraform) are highly preferred.
Requirements
What You'll Do:
- 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.
What You Need:
- A 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.
What’s In It for You:
- 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.