Job Seekers, Please send resumes to resumes@hireitpeople.com

Detailed Job Description:

• Bachelors or Masters Degree in a technology related field (e.g. Engineering, Computer Science, etc.)
• 8+ years of proven experience in implementing Big data solutions in data analytics space
• 2+ years of experience in developing ML infrastructure and MLOps in the Cloud using AWS Sagemaker
• Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required
• Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Pythons ML ecosystem (numpy, panda, sklearn, tensorflow, etc.)
• Experience with building data pipelines in getting the data required to build and evaluate ML models, using tools like Apache Spark or other distributed data processing frameworks
• Data movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies
• Strong knowledge of developing highly scalable distributed systems using Open-source technologies
• Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent)
• Solid experience in Agile methodologies (Kanban and SCRUM)
• Strong technical design and analysis skills
• Ability to deal with ambiguity and work in fast paced environment
• Experience supporting critical applications
• Familiarity with applied data science methods, feature engineering and machine learning algorithms
• Data wrangling experience with structured, semi-structured and unstructured data
• Experience building ML infrastructure, with an eye towards software engineering
• Excellent communication skills, both through written and verbal channels
• Excellent collaboration skills to work with multiple teams in the organization
• Ability to understand and adapt to changing business priorities and technology advancements in Big data and Data Science ecosystem