Streaming ML Engineer

OpenKyber LLC
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Tech stack

Training Data
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Big Data
Cloud Computing
Computer Programming
ETL
Data Transformation
Data Structures
Software Debugging
Distributed Systems
Python
Machine Learning
NumPy
Object-Oriented Software Development
Performance Tuning
Query Optimization
TensorFlow
Software Engineering
SQL Databases
Data Streaming
Data Processing
Google Cloud Platform
Cloud Platform System
Feature Engineering
PyTorch
Deep Learning
Pandas
Containerization
Scikit Learn
Kubernetes
Machine Learning Operations
Virtual Agents
Software Version Control
Data Pipelines
Docker

Requirements

Day-to-Day: Design, develop, and maintain AI-driven applications and services using Python and modern machine learning frameworks Write clean, efficient, and scalable code with a strong focus on algorithms, data structures, and performance optimization Build and optimize data pipelines for training, validating, and deploying machine learning models at scale Collaborate with data scientists, ML engineers, and product teams to translate business requirements into robust AI solutions Implement best practi ces in software engineering, testing, and version control to ensure high-quality deliverables Optimize AI/ML workloads for speed and scalability across distributed computing environments Stay current with advancements in AI, ML, and deep learning technologies, bringing innovative solutions into production systems Top Requirements 3+ years of hands on experience Proven experience as a Python Developer with hands-on expertise in building production-grade applications Must be hands-on with coding and demonstrate strong programming foundations (data structures, algorithms, object-oriented design) Strong background in AI/ML with experience using frameworks such as TensorFlow, PyTorch, or Scikit-learn Proficiency in data handling and manipulation using libraries like NumPy and Pandas Experience with SQL databases for managing and accessing training data Knowledge of model deployment and scaling in enterprise or cloud environments (AWS, Azure, or Google Cloud Platform) Familiarity with containerization and orchestration (Docker, Kubernetes) for AI/ML workloads (preferred) Strong debugging, optimization, and performance-tuning skills for both code and AI models Key Focus Areas Python Development: Core programming language for AI/ML applications AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn Data Pipelines: ETL, preprocessing, and feature engineering for large datasets SQL Databases: Schema design, query optimization, and handling structured data Enterprise-Scale AI: Building secure, reliable, and scalable AI solutions Hands-On Programming: Strong coding discipline with emphasis on maintainability and performance Cloud & Deployment (Preferred): AWS/Google Cloud Platform/Azure, Docker, Kubernetes

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