科技職缺
職缺列表
Architect
Principal Architect leading architectural initiatives across IT projects, translating business objectives into actionable plans and establishing reference architectures, governance, and delivery standards. Core stack spans AWS, Azure, GCP, Java, Go, React, Kubernetes, Docker, Terraform, and GenAI.
Lead AI/ML Engineer (GenAI & Architecture)
Lead the design and architecture of advanced AI/ML systems including GenAI, collaborating with data scientists and engineers to deploy ML models in production. Core stack spans Python, TensorFlow, Scikit-learn, and AWS, with deep learning and cloud deployment focus.
AI Architect
Remote freelance AI Architect shaping engineering architecture for high-scale systems, mentoring cross-functional teams, and driving AI/ML adoption using Python, AWS, Azure, Django, Docker, microservices, and MLOps.
ML Engineer
Senior ML Engineer shaping org-wide machine-learning strategy and architecture for mission-critical systems serving millions of users. Day-to-day work spans technical leadership, deep-learning model design and deployment (Python, TensorFlow, scikit-learn) on AWS, mentoring teams, and partnering with C-level leadership on roadmaps.
Lead AI/ML Engineer
Lead AI/ML Engineer defining multi-year technical strategy and architecting mission-critical AI/ML systems for millions of users while mentoring teams and partnering with C-level leadership. Core stack spans Python, PyTorch, TensorFlow, LLMs/GenAI, RAG, and NLP on AWS/GCP/Azure with Kubernetes, Docker, and MLOps/DevOps.
Machine Learning Engineer
A remote Machine Learning Engineer designs and implements ML models, collaborates with data scientists and engineers to integrate algorithms into products, and experiments to improve model performance. Core stack includes Python, TensorFlow, Scikit-learn, deep learning, NLP, and AWS.
Data Engineer
Remote Data Engineer designing, implementing, and maintaining scalable data pipelines and architectures while collaborating with data scientists and analysts on data modeling, storage optimization, and data quality across cross-functional teams.
Lead AI Engineer
Lead AI Engineer at Expertshub.ai architects and delivers end-to-end AI solutions across classical ML, deep learning, LLMs, and multimodal systems using Python, PyTorch/TensorFlow/JAX, while mentoring an AI/ML team and owning MLOps and production deployment on AWS/Azure/GCP.
AI/ML Lead Engineer
Remote AI/ML Lead Engineer driving the full ML lifecycle for banking clients, building LLM and agentic AI solutions on Gemini and Amazon Bedrock with strong MLOps practices.
Ai/ml Engineer
Onsite AI/ML Engineer building scalable computer vision and machine learning solutions for the ExpertsHub project, including object detection and image segmentation models using Python, TensorFlow, and PyTorch.
Full Stack Engineer
Full Stack Engineer driving technical strategy and architecture for systems serving millions of users. Day-to-day work spans JavaScript/Node.js/React development, microservices, distributed systems design, and collaboration with C-level leadership on platform modernization.
Senior Ai Engineer
Senior AI engineer building conversational AI systems, chatbots, and LLM applications using AWS Bedrock/Azure OpenAI, LangChain, LangGraph, LlamaIndex, RAG, and agent orchestration in Python on AWS/Azure.
Java Developer
Designs and develops scalable backend systems using Java and Spring Boot within a microservices architecture, building RESTful APIs and collaborating with cross-functional teams. Core stack: Java, Spring Boot, Microservices, REST APIs, Kafka/RabbitMQ, Docker, Kubernetes.
Sr. Ai/ml Engineer
Sr. AI/ML Engineer designing and optimizing LLM-based solutions through prompt engineering and experimentation. Day-to-day work involves Python development, managing Jupyter sandbox environments, building CI/CD pipelines, and working with AWS (including Bedrock) cloud infrastructure and Infrastructure-as-Code tools.
Ai/ml Engineer
Freelance remote AI/ML Engineer designing and implementing machine learning algorithms, optimizing models for performance, and collaborating with cross-functional teams. Core stack includes statistical modeling, REST APIs, NLP, deep learning, and cloud ML platforms (AWS SageMaker, Azure AI).
Applied AI Scientist
Applied AI Scientist designing, developing, and deploying machine learning models and NLP solutions in cloud environments using Python, TensorFlow or PyTorch, and Docker for feature engineering and data preprocessing.
Deep Learning Engineer
Designs, implements, and optimizes deep learning models using Python with PyTorch and TensorFlow, deploying and scaling them on AWS and GCP while collaborating with cross-functional teams on production integration.
Machine Learning Engineers
Remote US-based ML engineer designing, building, and maintaining machine learning models and pipelines using Python, Java, TensorFlow/PyTorch, SQL, and AWS/GCP/Azure cloud ML services.
Machine Learning (ML) Engineer
ML Engineer integrating and deploying AI/ML models into production at an AI company, optimizing inference pipelines, managing CI/CD, and building agentic and multimodal (text/vision/audio) workflows using Python, PyTorch, TensorFlow, FastAPI, LangGraph, and Docker/Kubernetes on AWS/GCP/Azure.
Machine Learning Engineer
Junior Machine Learning Engineer writing Python code with scikit-learn, TensorFlow, Pandas, and SQL to preprocess data, build models, and evaluate them. Hybrid role based in Pune, India, on a short-term freelance engagement supporting cross-functional teams.