
AI/ML Engineer
3 weeks ago
Responsibilities :
- Lead the design, development, and deployment of advanced machine learning models and algorithms for various applications.
- Perform comprehensive data analysis, feature engineering, and model training with large and complex datasets.
- Collaborate with cross-functional teams to understand business requirements and translate them into sophisticated technical solutions.
- Architect and deploy scalable AI/ML models, including large language models (LLMs) and transformer-based architectures.
- Implement MLOps best practices for CI/CD, automated model retraining, and lifecycle management.
- Optimize AI/ML pipelines for distributed computing, leveraging cloud platforms and
accelerators (GPUs/TPUs).
- Develop and maintain scalable advanced AI solutions such as retrieval-augmented generation (RAG) and fine-tuning techniques (LoRA, PEFT).
- Conduct thorough model evaluation, validation, and testing to ensure high performance and accuracy.
- Stay at the forefront of AI/ML advancements and integrate cutting-edge techniques into existing and new projects.
- Mentor and provide technical guidance to junior developers and team members.
- Author and maintain detailed documentation of processes, methodologies, and best practices.
- Implement and optimize cutting-edge deep learning models, such as Generative Adversarial Networks (GANs) and transformer architectures (e.g., BERT, GPT).
- Explore and implement federated learning approaches to build AI/ML models while preserving patient data privacy and security.
- Integrate explainable AI (XAI) techniques to ensure transparency and interpretability of machine learning models.
- Translate complex AI concepts into actionable insights for business stakeholders.
Required Qualifications :
- Bachelor's, Master's in Computer Science, AI, ML, Data Science, or related fields.
- 7+ years of experience with AI / ML solutions
- Extensive experience in developing and deploying machine learning models in a production
environment.
- Expertise in Python (NumPy, Pandas, scikit-learn), and proficiency in Java, Scala, or similar
languages.
- Deep understanding of deep learning frameworks (TensorFlow, PyTorch, JAX) and NLP libraries (Hugging Face Transformers).
- Hands-on experience with MLOps, including containerization (Docker, Kubernetes), CI/CD, and model monitoring.
- Well versed with Agentic AI.
- Deep understanding on Langchain ecosystem.
- Experience with distributed computing (Apache Spark, Ray) and large-scale dataset processing.
- Proficiency in vector databases (FAISS, Chroma DB, Pinecone) for efficient similarity search.
- Strong expertise in fine-tuning transformer models, hyperparameter optimization, and
reinforcement learning.
- In-depth experience with cloud platforms such as AWS, Azure, or Google Cloud for deploying AI solutions.
- Strong analytical, problem-solving, and communication skills to bridge technical and business perspectives.
Preferred Qualifications :
- Contributions to AI research, open-source projects, or top-tier AI conferences.
- Familiarity with generative AI, prompt engineering, and advanced AI topics like graph neural networks.
- Proven ability to scale AI teams and lead complex AI projects in high-growth environments
(ref:hirist.tech)
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