AI / Machine Learning Engineer

Description :Job SummaryWe are seeking an innovative and results-driven Artificial Intelligence Engineer to design, develop, deploy, and optimize AI/ML models and intelligent systems.The role involves working with large datasets, building machine learning and deep learning models, integrating AI solutions into production systems, and collaborating with cross-functional teams to solve complex business problems.Key Responsibilities :- Design, develop, train, evaluate, and deploy machine learning and deep learning models- Apply supervised, unsupervised, and reinforcement learning techniques- Build and optimize models for classification, regression, clustering, recommendation, and prediction- Collect, clean, preprocess, and analyze structured and unstructured data- Perform feature engineering and data augmentation to improve model performance- Work with large-scale datasets and distributed data processing systems- Deploy AI/ML models into production environments- Build and maintain scalable inference pipelines- Implement monitoring, versioning, and retraining strategies for deployed models- Collaborate with DevOps teams on CI/CD for ML (MLOps)- Develop deep learning models using CNNs, RNNs, Transformers, and LLM-based architectures- Work on NLP, Computer Vision, Speech Recognition, or Recommendation Systems- Fine-tune pre-trained models and foundation models- Integrate AI models with applications using REST APIs or microservices- Optimize model performance for latency, scalability, and cost- Work closely with software engineers to embed AI into products- Stay up to date with the latest AI/ML research, tools, and frameworks- Evaluate new algorithms and technologies and recommend adoption- Conduct experiments and document findings and best practicesRequired Skills & Qualifications :Technical Skills : - Strong proficiency in Python (mandatory); knowledge of Java/Scala is a plus- Hands-on experience with machine learning frameworks: TensorFlow, PyTorch, Scikit-learn- Experience with data processing libraries: Pandas, NumPy, Spark- Strong understanding of statistics, probability, linear algebra, and optimization- Experience with NLP (BERT, GPT, embeddings) and/or Computer Vision (OpenCV, CNNs)- Knowledge of LLMs, prompt engineering, RAG pipelines, and vector databases (FAISS, Pinecone, Milvus) (ref:hirist.tech)