Remote Software engineering Jobs · MLOps

• Lead AI initiatives and develop machine learning models to leverage organizational data effectively.
• Design, build, and maintain scalable ML infrastructure and pipelines for model training, evaluation, and deployment.
• Collaborate with Product, Clinical, Executive, Design, and Data teams to integrate ML solutions into workflows.

• Design, build, and ship production-grade ML models for high-impact use cases.
• Lead model architecture decisions, data pipeline design, and deployment strategies.
• Collaborate across product, engineering, and data teams to drive AI initiatives end-to-end.

• Build and optimize machine learning models analyzing security data, extracting actionable insights, and identifying trends.
• Deploy and maintain containerized workloads supporting machine learning development, deployment, and monitoring.
• Collaborate with cross-functional teams to design data pipelines efficiently processing petabytes of raw internet security data.

• Design, develop, and implement novel machine learning models and algorithms tailored to specific challenges.
• Engineer and deploy ML models into production environments, ensuring they are robust and scalable.
• Develop and maintain MLOps infrastructure for model versioning, continuous integration/delivery, and automated monitoring.

• Lead the development of advanced offline perception systems that generate high-quality annotations from sensor data.
• Design, implement, and deploy object detection, tracking, and fusion algorithms.
• Manage the full lifecycle of data preparation and curation, ensuring robust, scalable machine learning workflows.

Lead and scale a high-performing team in designing, building, and deploying cutting-edge Generative AI and machine learning solutions. Define the AI technical strategy, oversee platform development, and deliver AI solutions that drive measurable business impact. Lead a team of AI engineers, data scientists, and platform engineers while fostering a culture of innovation, operational excellence, and ethical AI adoption.

Design scalable software solutions with a focus on quality, performance, and maintainability. Lead software architecture decisions, ensuring the design aligns with business requirements and technical standards. Collaborate with Research Leads and Product Owners to gather requirements, design MLOps pipelines and coordinate the software delivery that adds value to the business.

As a senior machine learning engineer, you will work on the latest tools, frameworks and offerings while also being involved in enabling credible and collaborative problem solving to execute on a strategy. You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security.

We're looking for a Machine Learning Engineer who is deeply grounded in ML theory and excited to Design and implement ML solutions from ideation to production Fine-tune and integrate LLMs Deploy and monitor LLM-powered features at scale in real-world products Collaborate with engineers and product teams to build intelligent, user-facing features Write clean, scalable code and detailed technical documentation.

We are seeking a highly skilled Senior Software Engineer specializing in Machine Learning, with a focus on Natural Language Processing (NLP), to join our dynamic team. The ideal candidate will play a pivotal role in understanding business objectives and leveraging machine learning models to meet these goals effectively. This position requires a blend of expertise in data science and software engineering, along with a passion for staying at the forefront of machine learning advancements.