Python Machine Learning Developer

Python ML developer

-  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. • Ability to develop value-creating strategies and models that enable clients to innovate, drive growth and increase their business profitability • Good knowledge on software configuration management systems • Awareness of latest technologies and Industry trends • Logical thinking and problem solving skills along with an ability to collaborate • Understanding of the financial processes for various types of projects and the various pricing models available • Ability to assess the current processes, identify improvement areas and suggest the technology solutions • One or two industry domain knowledge • Client Interfacing skills • Project and Team management -  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.