Remote Data Science & Engineering Lead

Description:

• Lead the charge in AI and data innovation as the Data Science & Engineering Lead.
• Work hands-on with a talented team to build and deploy high-impact ML models, optimize data systems, and drive actionable insights.
• Design and implement supervised and unsupervised ML models to solve real-world business problems.
• Lead model development for advanced architectures in neural networks, including ANN, CNN, RNN, GAN, Transformers, and RESNet.
• Drive NLP advancements using tools like NLTK and neural-based language models.
• Oversee the development of computer vision models utilizing OpenCV for real-world applications.
• Lead time-series modeling projects for forecasting and anomaly detection.
• Utilize AI techniques like Retrieval-Augmented Generation (RAG), Chain of Thought (CoT), and Model of Alignment (MOA) to enhance model performance.
• Build and maintain scalable data pipelines for both streaming and batch processing.
• Architect and optimize lakehouse solutions using Delta/Iceberg and bronze-silver-gold architectures.
• Lead the development of ETL processes with tools like Airflow, DBT, and Airbyte to support data flow and transformation.
• Design and optimize database models for OLTP and OLAP systems using Snowflake, SQL Server, PostgreSQL, and MySQL.
• Develop NoSQL solutions leveraging MongoDB, DynamoDB, and ElasticSearch for unstructured data.
• Lead efforts in building cloud infrastructure, particularly in AWS or Azure, using services such as Lambda, API Gateway, Batch processing, Kinesis, and Kafka.
• Oversee MLOps pipelines for robust deployment of ML models in production with platforms like Sagemaker, Databricks, and Azure ML Studio.
• Develop and optimize business intelligence dashboards with tools like Tableau, QuickSight, and PowerBI for actionable insights.
• Implement GPU acceleration and CUDA for model training and optimization.
• Mentor junior team members in cutting-edge AI/ML techniques and best practices.

Requirements:

• Proven expertise in both supervised and unsupervised ML, advanced deep learning, including TensorFlow, PyTorch, and neural network architectures.
• Hands-on experience with machine learning libraries and tools such as Scikit-learn, Pandas, and Numpy.
• Proficiency in AI model development using LLM libraries like Langchain, Huggingface, and OpenAI.
• Strong MLOps skills, with experience deploying scalable pipelines in production using tools like Sagemaker, Databricks, and Azure ML Studio.
• Advanced skills in big data frameworks like Apache Spark, Glue, and EMR for distributed model training.
• Expertise in ETL processes and data pipeline development with tools like Airflow, DBT, and Airbyte.
• Strong knowledge in lakehouse architectures and experience with data quality frameworks like Great Expectations.
• Proficiency in cloud platforms (AWS preferred or Azure), with a deep understanding of services like IAM, VPC networking, Lambda, API Gateway, Batch, Kinesis, and Kafka.
• Proficiency with Infrastructure as Code (IaC) tools such as Terraform or CloudFormation for automation.
• Advanced skills in GPU acceleration, CUDA, and distributed model training.
• Demonstrated ability to architect and deploy scalable machine learning and data-intensive systems.
• Proficiency in database modeling for OLTP/OLAP systems and expertise with relational and NoSQL databases.
• Strong mentoring skills, with a proven track record of guiding junior team members in AI/ML best practices.
• Bachelor’s degree in a related field is required, with a Master’s or PhD in Data Science or a related field preferred.
• 7+ years of experience in data science, machine learning, or data engineering.
• AWS or Azure certification is strongly preferred.
• Strong communication and leadership skills with experience working cross-functionally to deliver high-impact data solutions.

Benefits:

• Join a collaborative culture that values meaningful work and innovation in AI and data.
• Enjoy competitive benefits that support your professional growth and well-being.
• Work remotely from India, providing flexibility in your work environment.
• Be part of a team that prioritizes dependability and exceptional results for clients.
• Contribute to a mission-driven organization that values diversity and equal employment opportunities.