Machine Learning Engineer Specialist

7 days ago


India Sense7ai Full time
Job Overview

We are looking for a highly skilled Machine Learning Engineer Specialist to join our team at Sense7AI Data Solutions. This role plays a critical part in designing, developing, and deploying state-of-the-art AI solutions using classical machine learning and cutting-edge generative AI technologies.

Key Responsibilities:
  • Design and build end-to-end AI/ML solutions tailored to real-world business challenges.
  • Leverage the latest advancements in Generative AI, LLMs, and multimodal models for intelligent applications.
  • Develop, fine-tune, and evaluate custom language models using transfer learning and prompt engineering.
  • Work with traditional ML models and deep learning architectures (CNNs, RNNs, Transformers) for diverse applications such as NLP, computer vision, and time-series forecasting.
  • Create and maintain scalable ML pipelines using MLOps best practices.
  • Collaborate with cross-functional teams (data engineers, product managers, business analysts) to understand domain needs and translate them into AI solutions.
  • Stay current on the evolving AI landscape, including open-source tools, academic research, cloud-native AI services, and responsible AI practices.
  • Ensure AI model transparency, fairness, bias mitigation, and compliance with data governance standards.
Requirements:
  • Education: Any degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • Experience: 3 – 5 years of hands-on experience in AI/ML solution development, model deployment, and experimentation.
  • Technical Proficiency:
    • Programming: Python (strong), familiarity with Bash/CLI, and Git.
    • Frameworks: TensorFlow, PyTorch, Hugging Face Transformers, Scikit-learn.
    • GenAI & LLM Tools: LangChain, OpenAI APIs, Anthropic, Vertex AI, PromptLayer, Weights & Biases.
    • Prompt Engineering: Experience crafting, testing, and optimizing prompts for LLMs across multiple platforms.
    • Cloud & MLOps: AWS/GCP/Azure (SageMaker, Vertex AI, Azure ML), Docker, Kubernetes, MLflow.
    • Data: SQL, NoSQL, BigQuery, Spark, Hadoop; data wrangling, cleansing, and feature engineering.
    • Strong grasp of model evaluation techniques, fine-tuning strategies, and A/B testing.
  • Preferred Qualifications:
    • Experience with AutoML, reinforcement learning, vector databases (e.g., Pinecone, FAISS), or RAG (Retrieval-Augmented Generation).
    • Familiarity with deploying LLMs and GenAI systems in production environments.
    • Hands-on experience with open-source LLMs and fine-tuning (e.g., LLaMA, Mistral, Falcon, Open LLaMA).
    • Understanding of AI compliance, data privacy, ethical AI, and explainability (XAI).
    • Strong problem-solving skills and the ability to work in fast-paced, evolving tech landscapes.
    • Excellent written and verbal communication in English.


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