The company is looking to solve the problem of architecting, coding, optimizing, and deploying Machine Learning models at scale using the latest industry tools and techniques.
Requirements
- Hands-on with Languages : Scala, Java , Python
- Strong computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
- Knowledge of Machine Learning or Data Science languages, tools, and frameworks, including SQL, Scikit-learn, NLTK, NumPy, Pandas, TensorFlow, and Keras.
- Experience with data processing tools and distributed computing systems and related technologies such as Spark, Hive, and Flink.
- Familiarity with cloud technologies, including AWS SageMaker tools and AWS Bedrock.
- Understanding of DevOps concepts, including CI/CD.
- Experience with software container technology, such as Docker and Kubernetes.
Responsibilities
- Design and build scalable, usable, and high-performance machine learning systems.
- Collaborate cross-functionally with product managers, data scientists, and engineers to understand, implement, refine, and design machine learning and other algorithms.
- Explore state-of-the-art technologies and apply them to deliver customer benefits.
- Discover, access, import, clean, and prepare data for machine learning.
- Work with AI scientists to create and refine features from underlying data and build pipelines to train and deploy models.
- Run regular A/B tests, gather data, perform statistical analysis, and draw conclusions on the impact of your models.
- Implement robust monitoring and alerting for deployed models to ensure continuous performance and detect anomalies.
Other
- BS, MS, or PhD degree in Computer Science or a related field, or equivalent practical experience.
- 3 to 5 year of experience
- Effectively communicate results to peers and leaders.
- Experience level max 5-6 yrs.
- ONLY W2 Candidates Required.
