Machine Learning Systems Research Intern at Red Hat working on AI inference and model optimization techniques. Collaborating with experts in the field while gaining hands - on experience in applied ML research.
About the role
- Machine Learning Engineer role at Level AI, innovating in speech AI and NLP space. Collaborate with experienced technologists to solve complex problems.
Responsibilities
- Big picture: Understand customers’ needs and innovate and use cutting-edge Machine Learning techniques to build data-driven solutions.
- Work on NLP problems across areas such as text classification, entity extraction, summarisation, generative NLP, and others.
- Collaborate with cross-functional teams to integrate/upgrade AI solutions into company’s products and services Optimise existing machine learning models for performance, scalability and efficiency.
- Build, deploy and own scalable production NLP pipelines.
- Build post-deployment monitoring and continual learning capabilities.
- Propose suitable evaluation metrics and establish benchmarks.
- Keep abreast of SOTA techniques in your area and exchange knowledge with colleagues.
- Desire to learn, implement and apply latest emerging model architectures (like LLMs), inference optimizations, distributed training, using open-source models, etc.
Requirements
- Bachelors in Computer Science or mathematics-related fields with 2+ years of experience in Machine Learning and NLP.
- Proficient in Python, NLP knowledge and practical experience in solving NLP problems in areas such as text classification, entity tagging, information retrieval, question-answering, natural language generation, clustering, etc.
- Knowledge and experience with data engineering, basic machine learning concepts, data mining, feature extraction, pattern recognition, etc.
- Knowledge and hands-on experience with Transformer-based Language Models like BERT, DeBERTa, Flan-T5, GPT, Llama, Gemma, DeepSeek, etc.
- Deep familiarity with Model Training concepts, model inference optimisations, GPUs, etc.
- Experience with Deep Learning frameworks like Pytorch and common machine learning libraries like scikit-learn, numpy, pandas, NLTK, transformers, etc.
- Experience with ML model deployments using REST API, Docker, Kubernetes, etc.
- Knowledge of cloud platforms (AWS/Azure/GCP) and their machine learning services is desirable.
- Knowledge of basic Data Structures and Algorithms.
- Knowledge of Multimodal models is a plus
- Knowledge of real-time streaming tools/architectures like Kafka, Pub/Sub is a plus.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Senior Machine Learning Engineer focused on Machine Learning Ops for Autodesk software products. Building production infrastructures, ensuring AI - powered experiences, and collaborating with cross - functional teams.
Senior Machine Learning Engineer developing and deploying machine learning models for autonomous trucks. Collaborating with various teams to enhance safe and efficient decision - making in freight environments.
AI Engineer at PayPal designing, building, and deploying autonomous AI systems powered by LLMs. Collaborating across teams on AI engineering, distributed systems, and product development.
Machine Learning Engineer designing and deploying advanced training capabilities to support U.S. Navy operational readiness. Collaborate on machine - learning models to enhance combat system training environments.
Cloud MLOps Engineer supporting Data Science and Engineering teams by automating CI/CD pipelines and managing multi - cloud infrastructure for ML production.
Lead development of Agentic AI capabilities and LLM applications for multiple mission management applications. Mentor teams to implement ML algorithms addressing customer challenges.
Staff AI/ML Engineer at CACI responsible for developing AI/ML algorithms and analyzing datasets. Join a high - performing team supporting national safety missions.
AI/ML Engineer at CACI developing machine learning algorithms for multiple applications. Collaborating with a research team to implement cutting - edge AI/ML solutions for customer missions.
Senior Computer Vision AI/ML Engineer leading a team in AI/ML algorithm implementation for remote sensing solutions. Responsibilities include training models and analyzing datasets with a focus on defense and commercial applications.