
Advanced Machine Learning Specialist
2 days ago
Data Science Leader:
- AI/ML Development & Research
- Design, develop, and deploy advanced machine learning and deep learning models to solve complex business problems.
- Implement and optimize Large Language Models (LLMs) and Generative AI solutions for real-world applications.
- Build agent-based AI systems with autonomous decision-making capabilities.
- Conduct cutting-edge research on emerging AI technologies and explore their practical applications.
- Perform model evaluation, validation, and continuous optimization to ensure high performance.
Cloud Infrastructure & Full-Stack Development:
- Architect and implement scalable, cloud-native ML/AI solutions using AWS, Azure, or GCP.
- Develop full-stack applications that seamlessly integrate AI models with modern web technologies.
- Build and maintain robust ML pipelines using cloud services (e.g., SageMaker, ML Engine).
- Implement CI/CD pipelines to streamline ML model deployment and monitoring processes.
- Design and optimize cloud infrastructure to support high-performance computing workloads.
Data Engineering & Database Management
- Design and implement data pipelines to enable large-scale data processing and real-time analytics.
- Work with both SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra) to manage structured and unstructured data.
- Optimize database performance to support machine learning workloads and real-time applications.
- Implement robust data governance frameworks and ensure data quality assurance practices.
- Manage and process streaming data to enable real-time decision-making.
Leadership & Collaboration
- Mentor junior data scientists and assist in technical decision-making to drive innovation.
- Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to develop solutions that align with organizational goals.
- Present findings and insights to both technical and non-technical audiences in a clear and actionable manner.
- Lead proof-of-concept projects and innovation initiatives to push the boundaries of AI/ML applications.
Required Qualifications:
- Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related field.
- 5+ years of hands-on experience in data science and machine learning, with a focus on real-world applications.
- 3+ years of experience working with deep learning frameworks and neural networks.
- 2+ years of experience with cloud platforms and full-stack development.
Benefits:
- Expertise in Scikit-learn, XGBoost, LightGBM, and advanced ML algorithms.
- Deep Learning: Expertise in TensorFlow, PyTorch, Keras, CNNs, RNNs, LSTMs, and Transformers.
- Large Language Models: Experience with GPT, BERT, T5, fine-tuning, and prompt engineering.
- Generative AI: Hands-on experience with Stable Diffusion, DALL-E, text-to-image, and text generation models.
- Agentic AI: Knowledge of multi-agent systems, reinforcement learning, and autonomous agents.
Non Negotiables:
- Cloud Infrastructure - ML/AI solutions on AWS, Azure, or GCP
- Build and maintain ML pipelines using cloud services (SageMaker, ML Engine, etc.)
- Implement CI/CD pipelines for ML model deployment and monitoring
- Work with both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, etc.)
- Machine Learning: Scikit-learn
- Deep Learning: TensorFlow
- Programming: Python (expert), R, Java/Scala, JavaScript/TypeScript
- Cloud Platforms: AWS (SageMaker, EC2, S3, Lambda)
- Vector databases and embeddings (Pinecone, Weaviate, Chroma)
- Knowledge of LangChain, LlamaIndex, or similar LLM frameworks.
If interested, please share your resume to sunidhi.manhas@portraypeople.com
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