Machine Learning Engineer - Python/Scala @ Axycube Solutions

Job Description

Your Role And Responsibilities We are looking for a highly skilled and experienced Senior Machine Learning and Data Engineer to join our team of AI experts. You will be responsible for designing, implementing and optimizing our data and machine learning pipelines across a wide variety of applications. The ideal candidate is an experienced data and ML pipeline builder who enjoys optimizing data and machine learning systems and building them from the ground up. The ML Data Engineer will support our software developers and data scientists in embedding AI into our products and will ensure that our data and ML delivery architecture is consistent across projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing and re-designing our data and ML architecture to support our next generation of products and data initiatives. Key Responsibilities Design and develop. robust, scalable, and high-performance data and machine learning pipelines, ensuring data integrity and reliability throughout the process. Collaborate with cross-functional teams, including data scientists, product managers, and software engineers, to understand data and machine learning requirements and deliver optimal solutions. Experience delivering and maintaining productionized end-to-end Machine Learning solutions, form data preparation, experimentation, model training, model serving, and model update Design solutions that ensuring efficient data storage, retrieval, and processing capabilities using modern data lakehouse and data fabric systems. Develop and implement data transformation and cleansing processes to ensure data quality and consistency. Optimize and fine-tune data and machine learning pipelines for improved performance, scalability, and reliability. Collaborate with the DevOps team to ensure data security, privacy, and compliance with relevant regulations and best practices. Document technical specifications, system architecture, and data flows to facilitate knowledge sharing and maintain a well-documented system. Stay updated with emerging technologies, industry trends, and best practices in data engineering, and proactively introduce new tools, frameworks, and techniques to enhance data processing capabilities. Required Technical And Professional Expertise 5+ years as a Data and Machine Learning Engineer or similar role with a focus on designing and developing end-to-end enterprise data and machine learning pipelines Knowledge of data best practices and MLOps/Dev operations in SaaS and hybrid environments 5+ years of Python, Scala or Java development experience Ability in managing and communicating data and machine learning pipeline plans to internal clients Experience building, running, and maintaining productionized Machine Learning models using a well-designed MLOps approach Experience working with both batch and streaming data Experience with machine learning frameworks like PyTorch, Tensorflow and scikit-learn Experience with cloud-based platforms and services (e.g., IBM, AWS, Azure, Google Cloud). Strong expertise in working with big data technologies and frameworks like Hadoop, Spark, or Kafka. Strong understanding of data governance, data security, and data privacy best practices. Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders. Preferred Technical And Professional Expertise Experience designing, building, and maintaining data processing and machine learning systems working in containerized environments (Docker, OpenShift, k8s) Experience working with both batch and streaming data ingestion Experience building reusable and reliable workflows and pipelines using workflow engines (Argo, Tekton, etc.) Experience developing or leveraging automated platforms for model observability, model quality and drift and systems to automatically identify and correct issues. Experience developing or leveraging automated platforms for data observability, data quality and drift and systems to automatically identify and correct data issues. Want to know what it s like to be an IBMer Role : Machine Learning Engineer Salary : Not Disclosed by Recruiter Industry : IT Services & Consulting Department : Data Science & Analytics Role Category : Data Science & Machine Learning Employment Type : Full Time, Permanent Key Skills Data Engineering, MLOps, PyTorch, Machine Learning, Python Tensorflow, data security, SCALA, data governance, Data processing (ref:hirist.com

Employement Category:

Employement Type: Full time
Industry: Others
Role Category: Client ServerWeb / Mobile Technologies
Functional Area: Not Applicable
Role/Responsibilies: Machine Learning Engineer - Python/Scala

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Keyskills:   Data Engineering Machine Learning Python SCALA Data security Data governance Data processing MLOps PyTorch Tensorflow