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Job Type: Full-time (Contract for : 3 Months)
Job mode: Remote
Sense7AI Data Solutions is seeking a highly skilled and forward-thinking AI/ML Engineer to join our dynamic team. You will play a critical role in designing, developing, and deploying state-of-the-art AI solutions using both classical machine learning and cutting-edge generative AI technologies. The ideal candidate is not only technically proficient but also deeply familiar with modern AI tools, frameworks, and prompt engineering strategies.
Key Responsibilities
Design, build, and deploy end-to-end AI/ML solutions tailored to real-world business challenges.
Leverage the latest advancements in Generative AI, LLMs (e.g., GPT, Claude, LLaMA), 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.
Required Skills & Qualifications
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., Milvus, 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.
Job Type: Full-time
Contract length: 3 months
AIML,LLM,NLP,GenAI,AI ,ML Models,TENSORFLOW,PYTORCH
Full Time