Machine Learning Engineer

What You’ll Do
We are looking for a Machine Learning Engineer specializing in NLP, document classification, and large-scale data processing. You will work on applying LLMs, NLP, and ML techniques to categorize and process extracted data. Your work will power an intelligent search system and help organize massive amounts of structured and unstructured information.

• 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.

What You’ll Bring

• 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.

Nice to Have

• 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.