Data Scientist AI/ML

Job Title: Data Scientist AI/ML

Experience: 8 10+ Years
Location: Onsite / Hybrid / Remote (customizable)
Interview: Onsite interview can be scheduled at your local state
Role Type: Full-Time

Job Description:

We are seeking an experienced Data Scientist with strong expertise in Artificial Intelligence and Machine Learning to join our team. The ideal candidate will design, build, and deploy end-to-end AI/ML models, work with large datasets, and collaborate closely with engineering and product teams to deliver scalable data-driven solutions.

Key Responsibilities:

• Develop, train, and optimize machine learning and deep learning models for prediction, classification, NLP, computer vision, and recommendation use cases.

• Analyze large, complex datasets and extract actionable insights using statistical and ML techniques.

• Build end-to-end data pipelines, including data preprocessing, feature engineering, model training, testing, and deployment.

• Implement AI/ML models into production using tools such as TensorFlow, PyTorch, Scikit-learn, etc.

• Work with cross-functional teams (data engineering, product, analytics) to gather requirements and deliver AI-driven solutions.

• Conduct model performance monitoring, retraining, fine-tuning, and improvements.

• Communicate complex findings to business stakeholders through clear presentations, dashboards, and reports.

• Stay updated with the latest AI/ML research trends and apply them to real-world projects.

Required Skills & Qualifications:

• 8+ years of experience as a Data Scientist, with hands-on expertise in ML, AI, deep learning, and statistical modeling.

• Strong proficiency in Python, along with ML libraries such as Scikit-learn, TensorFlow, Keras, PyTorch.

• Experience with NLP, LLMs, neural networks, and advanced ML algorithms.

• Hands-on experience with data pipelines, ETL processes, and model deployment.

• Strong knowledge of cloud platforms like AWS, Azure, or Google Cloud Platform.

• Proficiency in SQL, data modeling, and working with structured/unstructured datasets.

• Strong understanding of algorithms, data structures, and mathematics (statistics, probability, linear algebra).

• Excellent analytical, problem-solving, and communication skills.

Preferred Skills:

• Experience with MLOps, CI/CD for ML, and tools like MLflow, Kubeflow, or SageMaker.

• Experience with big data technologies (Spark, Hadoop).

• Knowledge of generative AI, LLM fine-tuning, vector databases, and embeddings.

• Experience in deploying models using Docker, Kubernetes, REST APIs.