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Lead Data Scientist

Karnataka, India (On-site)

Lead Data Scientist

2 Months ago • 5-8 Years • Artificial Intelligence • Undisclosed

About the job

15 skills required for this role

Add these skills to join the top 1% applicants for this job

python

pytorch

deep-learning

azure

aws

data-science

neural-networks

algorithms

kubernetes

pandas

computer-vision

scikit-learn

numpy

model-deployment

communication

Job Description

Lead Data Scientist responsible for developing and deploying advanced AI models using Python and PyTorch, including LLMs. This role involves collaborating with cross-functional teams, implementing MLOps practices, and monitoring model performance. Responsibilities include designing and optimizing machine learning and deep learning models, deploying models on cloud platforms (AWS, Azure, Google Cloud), and staying current with AI trends. The ideal candidate will possess strong leadership, communication, and analytical skills, along with expertise in Python, PyTorch, and cloud technologies.

Must have:

Python (NumPy, pandas, scikit-learn, PyTorch)
ML/DL model building & deployment
Cloud platform experience (AWS, Azure, GCP)
LLM implementation and fine-tuning
MLOps & model monitoring
Strong communication & leadership skills

Good to have:

Data Engineering knowledge
Experience with specific cloud services (EC2, S3, Lambda, Kubernetes)

About the job

Job Description

We are seeking an experienced talent of 5- 8 years with a strong background in Python and ML to join our dynamic team. In this role, you will lead our data science initiatives, developing and deploying advanced AI models to solve complex problems.

Responsibilities

Develop Advanced Machine Learning Models: Design, implement, and optimize machine learning and deep learning models using Python and PyTorch.

Implement LLMs: Research, fine-tune, and deploy Large Language Models to improve product features and user experience.

Cloud Deployment: Deploy and manage machine learning models on cloud platforms (e.g., AWS, Azure, Google Cloud) to ensure scalability and reliability.

Collaborate Cross-functionally: Work closely with engineering, product, and business teams to integrate AI solutions into our products and services.

Stay Current with AI Trends: Keep abreast of the latest developments in AI, deep learning, and cloud technologies to drive innovation.

Establish Best Practices: Implement MLOps practices for continuous integration and deployment of models, ensuring efficient workflow.

Performance Monitoring: Develop monitoring tools to evaluate the performance of deployed models and iterate as necessary.

Communicate Insights: Present complex data findings in a clear and concise manner to stakeholders at all levels.

Requirements

Educational Background: Master's in Computer Science, Data Science, Machine Learning, or a related field.

Extensive Python Expertise: Proficient in Python programming with experience in libraries such as NumPy, pandas, scikit-learn, and PyTorch.

Experience with PyTorch: Proven track record in building and deploying models using PyTorch, including working with NLP techniques and/or Computer Vision.

Cloud Services Proficiency: Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud, including services such as EC2, S3, Lambda, and Kubernetes.

Machine Learning Expertise: Strong understanding of machine learning algorithms, neural networks, and deep learning architectures.

Leadership Skills: Demonstrated ability to lead and manage technical teams, with strong project management skills.

Data Engineering Knowledge: Familiarity with data pipelines, ETL processes, and big data technologies.

MLOps Experience: Knowledge of MLOps tools and practices for model deployment, version control, and monitoring.

Strong Analytical Skills: Excellent problem-solving abilities with a focus on translating business problems into data-driven solutions.

Excellent Communication: Ability to effectively communicate complex technical concepts to both technical and non-technical audiences.

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