Ml Engineer

6 days ago

Hyderabad, Telangana, India Solix Technologies Full time ₹ 1,04,000 - ₹ 1,30,878 per year

Solix Technologies Inc. is a leading provider of big data applications for enterprise archiving, data privacy, and advanced analytics. We are on a mission to help organizations manage and leverage their data for maximum value, efficiency, and compliance.

Job Summary:

We are seeking a highly skilled and motivated Machine Learning Engineer with hands-on experience in Natural Language Processing (NLP) and Large Language Models (LLMs). You will play a key role in designing, developing, and deploying scalable ML/NLP solutions that drive intelligent automation and data insight across our platforms.

Key Responsibilities:

  • Design and develop machine learning models, particularly in the domain of NLP and LLMs.
  • Fine-tune, evaluate, and deploy transformer-based models (e.g., BERT, GPT, T5, LLaMA, etc.).
  • Apply techniques such as named entity recognition (NER), text classification, semantic search, summarization, and question answering.
  • Work with large-scale datasets to extract insights and build data pipelines.
  • Collaborate with cross-functional teams including data engineers, product managers, and software developers.
  • Conduct experiments, model training, and optimization to improve accuracy and performance.
  • Stay up-to-date with the latest research in NLP, LLMs, and machine learning.

Required Skills and Experience:

  • Bachelor's or Masters degree in Computer Science, Data Science, AI/ML, or a related field.
  • Minimum 5+ years of hands-on experience with NLP and LLMs
  • Proficient in Python and ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers.
  • Strong understanding of modern NLP techniques (tokenization, embeddings, attention mechanisms, etc.).
  • Experience with ML lifecycle including model development, evaluation, and deployment (MLOps).
  • Familiarity with data handling libraries (Pandas, NumPy) and cloud platforms (AWS, GCP, or Azure).
  • Good understanding of data preprocessing, feature engineering, and model validation techniques.
  • Experience with open-source LLM fine-tuning and deployment.
  • Knowledge of vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG).
  • Prior experience with large-scale data systems or enterprise data environments.
  • Published papers or open-source contributions in the ML/NLP space.

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