Machine Learning Engineer

Summary

Join Tekmetric, a rapidly growing cloud-based auto-repair shop management system company, as a Machine Learning Engineer specializing in NLP. You will develop and train NLP & ML models for document classification, text extraction, and entity recognition, working with LLMs and large-scale data processing. This role involves building pipelines, applying OCR techniques, and deploying models in production using Kubernetes and AWS. You will collaborate with data engineers and utilize Spark for large-scale processing. The ideal candidate possesses 3+ years of experience in Machine Learning & NLP and strong Python skills. Tekmetric offers a dynamic work environment and a comprehensive benefits package.

Requirements

• 3+ years of experience in Machine Learning & NLP
• Strong Python skills and experience with ML/NLP frameworks like Hugging Face, spaCy, NLTK, TensorFlow, PyTorch etc
• Familiarity with transformer-based architectures (BERT, GPT, T5, etc.)
• Experience with text classification, embeddings
• Knowledge of OCR (Tesseract, Amazon Textract, or OpenCV-based techniques)
• Hands-on experience with AWS services, Kubernetes, and workflow orchestration (Airflow)
• Strong understanding of information retrieval, search ranking, and ElasticSearch/OpenSearch

Responsibilities

• Develop and train NLP & ML models for document classification, text extraction, and entity recognition
• Experiment with LLMs (GPT, Llama, Claude, etc.), embeddings, transformers, and vector databases
• Build pipelines that combine rule-based methods with ML models for classification
• Apply OCR techniques to extract structured data from PDFs and scanned documents
• Fine-tune and optimize models for scalability, latency, and cost-efficiency
• Deploy ML models in production using Kubernetes, AWS (SageMaker, Lambda, EMR), and Airflow
• Collaborate with data engineers to integrate ML models into search APIs and data pipelines
• Utilize Spark (EMR) or distributed computing for large-scale ML processing

Preferred Qualifications

• Experience fine-tuning LLMs for domain-specific applications
• Experience with RAG and vector databases (FAISS, Pinecone, Weaviate, Vespa, etc.)
• Working knowledge of knowledge graphs, embeddings, or multimodal ML
• Experience optimizing ML models for real-time processing in production environments

Benefits

• Flexible and remote work opportunities
• Generous PTO
• Exceptional leave programs for all of life’s moments: maternity, paternity and parental bonding, as well as medical leave to care for yourself or loved ones
• Excellent Medical, Dental, Vision and Prescription Drug Coverage
• 401(k) Retirement Savings Plan with a 6% Match
• Employer covered STD, LTD, Life and AD&D Insurance Programs
• Up to $60 monthly for wellness expenses and activities
• Education Assistance- includes undergraduate/graduate courses and continuing education