Remote Machine Learning Engineer Jobs

- BS/MS in Computer Science, Statistics, Electrical/Computer Engineering, Mathematics, or a related field - 5+/4+ years of experience after BS/MS - Strong software engineering basics - Knowledge of common challenges in training ML models and solutions to them - Familiarity with the technical details of deep learning concepts, such as Transformers, Retrieval-Augmented Generation (RAG), mixture of experts (MoE) - Proficiency in data/ML libraries such as pandas, transformers, and torch - Hands-on e…

Candidates must possess a Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, or Mathematics. A minimum of 7 years of experience in data science and machine learning, with a focus on real-time ML models, preferably in tech or marketplace environments, is required. Expertise in machine learning and deep learning, including a good working knowledge of large language models, is essential. Proven experience deploying impactful machine learning models into production, prof…

Candidates should possess a strong foundation in computer science, including knowledge of data structures, algorithms, and design patterns, along with experience in developing and maintaining production machine learning systems. Expertise in Python and cloud technology stacks like GCP or AWS is required, as well as an interest in architecting machine-learning platforms and a familiarity with tools such as Spark, Kubernetes, Airflow, and MLFlow.

The candidate should have strong experience in training large-scale machine learning systems, particularly in STT or related speech domains. Proficiency with orchestration and infrastructure tools like Kubernetes, Docker, and Prefect, as well as familiarity with ML lifecycle tools such as MLflow, is required. Experience building internal tools or dashboards for non-technical users is also necessary.

- Experience designing and leading end-to-end ML systems - Experience with destination inference, anomaly detection, and modality prediction - Experience partnering with Data Science to translate modeling research into production systems - Experience building and maintaining ML pipelines - Experience integrating ML into user-facing features - Experience championing operational excellence through model monitoring and drift detection - Experience contributing to architectural strategy

Candidates should possess a Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent hands-on experience. They are expected to demonstrate exceptional problem-solving abilities and strong communication skills to influence decisions and drive alignment across teams. A minimum of 5 years of experience in building and delivering robust, scalable, and highly reliable services in production environments is required, along with a deep passion for technical exce…

- Experience designing and deploying ML models - Experience building and productionizing real-time model APIs - Experience integrating model outputs into user-facing features - Experience contributing to the development of self-serve ML infrastructure - Experience designing and implementing feature pipelines, model training workflows, and scalable inference systems - Experience monitoring and maintaining model health, performance, and drift - Partnering with Product, Data Science, and Cloud Engi…

Candidates must possess a PhD in Physics or a related field and have a deep understanding of machine learning algorithms and techniques, including experience in building and deploying models from scratch. Strong analytical and problem-solving skills are essential, along with a passion for the real-world application of machine learning and a desire to make a significant impact on large-scale business initiatives.

Candidates must possess a Master's or Ph.D. in Computer Science, Engineering, or a related field, with over 6 years of experience as a Machine Learning Engineer. Proficiency in Python and ML libraries such as TensorFlow, PyTorch, and scikit-learn is essential, alongside extensive experience with cloud platforms like AWS, GCP, or Azure and distributed computing frameworks like Spark and Kubernetes. A proven history of implementing end-to-end machine learning pipelines, model optimization, version…

Candidates should possess deep technical expertise in machine learning and a passion for solving novel challenges. An enthusiasm for helping scientists communicate groundbreaking research faster and more effectively is essential. A scientific and research background is a nice to have.

Candidates should have a Bachelor's or Master’s degree in Computer Science, Engineering, Mathematics, or a related field, with a Ph.D. considered a plus. They must possess 5+ years of experience in machine learning and data-related roles and have proven experience as a Machine Learning Engineer or in a similar position. Strong programming skills in Python and familiarity with ML frameworks like TensorFlow or PyTorch are required. Additionally, experience with data processing, data analytics, and…

Candidates should have 4-5 years of professional experience in Python, with at least 3 years focused on machine learning and production deployment of ML models. Strong hands-on skills with PyTorch, TensorRT, and Python are required, along with proficiency in JavaScript. Familiarity with object detection, classification, segmentation, YOLO, VLMs, and SAM is also necessary. Experience working in startups or high-ownership roles, and comfort with autonomy, ambiguity, and rapidly shifting priorities…

- B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field - 1-2 years of hands-on industry experience with demonstrable ownership and delivery - Strong understanding of machine learning fundamentals, data pipelines, and model evaluation - Proficiency in Python and ML/data libraries (NumPy, pandas, scikit-learn) - Working knowledge of LLM core concepts, prompt design, and agentic design patterns - Strong communication skills and a passion for shaping emerging AI paradigms

- 3+ years of industry experience in ML Engineering in cloud-native environments - In-depth knowledge of Python and Javascript/Typescript (preferable), or other modern languages in the ML domain - Experience with infrastructure and DevOps tools such as Kubernetes, Docker, and Ansible - Experience in distributed systems, storage systems, and databases - Strong knowledge of cloud computing platforms such as AWS (preferable), GCP, and Azure - Experience with monitoring, tracing, and logging tools s…

- 8+ years of experience in applied Machine Learning - Ph.D. or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field - Deep expertise in mainstream RecSys model architecture (e.g. two-tower, transformer-based model, multi-task learning, wide and deep etc.) - Strong proficiency in Python and ML frameworks such as PyTorch, JAX, or TensorFlow - Extensive experience building performant machine learning systems at scale and have driven execution from idea…