Data Science Engineer

AIML JD

Experience:

Total 12+ industry experience.

5+ year experience in applying machine learning techniques to real business problems.

Key Qualifications:

- Excellent Python programming and debugging skills. (Refer to Pytho JD given below)

- Proficiency with SQL, relational databases, & non-relational databases

- Passion for API design and software architecture.

- Strong communication skills and the ability to naturally explain difficult technical topics to everyone from data scientists to engineers to business partners

- Experience with modern neural-network architectures and deep learning libraries (Keras, TensorFlow, PyTorch).

- Experience unsupervised ML algorithms.

- Experience in Timeseries models and Anomaly detection problems.

- Experience with modern large language model (Chat GPT/BERT) and applications.

- Expertise with performance optimization.

- Experience or knowledge in public cloud AWS services - S3, Lambda.

- Familiarity with distributed databases, such as Snowflake, Oracle.

- Experience with containerization and orchestration technologies, such as Docker and Kubernetes.

Role Description:

- Managing large machine learning applications and designing and implementing new frameworks to build scalable and efficient data processing workflows and machine learning pipelines.

- Build the tightly integrated pipeline that optimizes and compiles models and then orchestrates their execution.

- Collaborate with CPU, GPU, and Neural Engine hardware backends to push inference performance and efficiency

- Work closely with feature teams to facilitate and debug the integration of increasingly sophisticated models, including large language models

- Automate data processing and extraction

- Engage with sales team to find opportunities, understand requirements, and translate those requirements into technical solutions.

- Develop reusable ML models and assets into production.

Python JD

Detailed JD *(Roles and Responsibilities) " • 2+ years Python/Data Science skillset

• 5 years of experience with building data pipelines, data processing and reporting using Python
• Python libraries numpy, Pandas, matplotlib, seaborn, Scikitlearn Data Science Data Manipulation, Wrangling, time series forecasting etc prior experience in any data science project building data pipelines, data processing and reporting
• Experience of using Agile based development methodologies
• Good understanding software development and Enterprise architecture patterns
• Hands-on experience with open source big data technologies
• Data processing experience with Streaming, data wrangling, crawling using Python libraries
• Expertise and understanding of common methods in data transformation
• Ability to understand API Specs, determine relevant API calls,
• ETL i.e. Extract->Transform->Load data and implement SQL friendly data structures
• Experience on using GIT , resolving conflicts, working with branches
• Understanding and exposure to file formats such as Apache AVRO, Parquet"