Machine learning engineer • usa
We are seeking a Senior ML Engineer to join our team of dedicated machine learning and software engineers.This role involves timely engineering, system development, ML model assessment, constructin...Show more
We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions.In this role, you'll have the opportunity to shape and create our ma...Show more
We are seeking a skilled and experienced Machine Learning (ML) Engineer to join our team in a customer-facing role.You will architect and implement innovative ML solutions, working closely with dat...Show more
We are seeking a skilled Machine Learning Engineer (MLOps) to support the full lifecycle of machine learning models, including design, development, deployment, and maintenance.This role focuses on ...Show more
Work closely with AI and imaging scientists in machine learning work streams including but not limited to semantic segmentation, object detection and classification.Work closely with Client and dat...Show more
Company Description The Ikigai platform unlocks the power of generative AI for tabular data.We enable business users to connect disparate data, leverage no-code AI/ML, and build enterprise-wide AI ...Show more
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products.We believe that oddsmaking is a challenge rooted in engi...Show more
Pittsburgh, Pennsylvania (On-site).We are seeking a highly skilled professional to drive continuous support of production AI models while collaborating closely with a large team of data scientists ...Show more
Strong computer science fundamentals such as algorithms, data structures, multithreading, object-oriented development, distributed applications, client-server architecture.Design and implement Mach...Show more
ProSidian Seeks a Machine Learning Engineer | Data Management & Business Intelligence - Predictive Workforce Analytics [NSF0117117] for Program Support on a Exempt W2: No Overtime Pay Basis located...Show more
Machine Learning Engineer Richmond, Virginia (5 Days Onsite) need local within commute About the Role We are seeking a Machine Learning Engineer with expertise in agentic AI systems to design, buil...Show more
At Replica we're building the world's leading AI Voice Platform for the next generation of games and movies.We're always on the lookout for great talent to join our team (remotely or at our office)...Show more
We specialize in providing cutting-edge machine learning solutions to our clients in various industries.We are currently seeking a highly skilled and motivated Machine Learning Engineer to join our...Show more
Machine Learning Engineer .AI-powered software for the nuclear and utility industries—tools that keep critical infrastructure reliable, efficient, and safe.Our software integrates AI-driven workflo...Show more
As a Machine Learning Engineer on the Foundations team you will own the entire ML lifecycle: creating POCs, building production-ready systems, deployment, monitoring and maintenance.In this role yo...Show more
It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at.Were a team of engineers, clini...Show more
A client of Innova Solutions is immediately hiring for a.Position type: Full time, Contract.As a Machine Learning Engineer,you will:.Design and implement agentic AI systems capable of planning, too...Show more
Our mission is to make buying, selling, renting, and living in homes easier and more rewarding for everyone.Building your career? Build it better at.Machine Learning Engineer at (View all jobs) (.A...Show more
The average salary range is between $ 124,693 and $ 200,000 year , with the average salary hovering around $ 154,997 year .
Description
We are seeking a Senior ML Engineer to join our team of dedicated machine learning and software engineers. This role involves timely engineering, system development, ML model assessment, constructing data pipelines, composing prototypes, evaluation, operationalization.
Looking for individuals skilled in classical and deep learning, able to build and implement ML solutions for production environments. If you thrive on delivering innovative customer features, adopting new technologies, and contributing to high-visibility projects, this role may be a good match. The atmosphere is dynamic, fast-paced, creative, collaborative, and data-centric.
What you’ll do
Contribute to the backend services supporting ML and Generative-AI functionalities.
Build, develop, implement, and evaluate machine learning models using classical and deep learning approaches, as well as GenAI.
Collaborate with cross-functional teams to integrate ML solutions into existing products and services.
Analyze and improve efficiency, accuracy, scalability, and stability of AI-enabled workflows.
Stay current with the latest advancements in ML and AI technologies.
Guide and support junior team members to aid in the overall development of the ML team.
What you need to succeed
Required Qualifications:
Completed a degree in Computer Science, Machine Learning, or a related field.
5+ years of experience in machine learning engineering roles.
Strong software engineering skills, including version control, code review, and CI/CD practices.
Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, scikit-learn, Sagemaker.
Experience in developing and deploying ML models in production environments.
Familiarity with cloud platforms (, AWS, GCP, Azure) for ML deployment.
Strong understanding of data structures, algorithms, and system development.
Strong leadership and team-building skills.
Excellent communication and presentation skills.
Familiarity with Generative AI technologies and applications is advantageous.
Familiarity with Retrieval-Augmented Generation (RAG) and other contemporary NLP methods is advantageous.
Having experience with MLOps practices and tools is advantageous.
Having a background in Recommendation Systems is advantageous.
