Companies in Need of Machine Learning Expertise: 12 Firms Seeking Engineers
In the rapidly evolving world of technology, the demand for machine learning (ML) engineers is on the rise. These professionals play a crucial role in bridging the gap between data science and production systems, ensuring that ML models are not only accurate but also robust, scalable, and aligned with business goals.
Major tech companies like Google and Adobe are actively recruiting ML engineers to drive innovation in their projects. For instance, Google is hiring ML engineers for its Personal AI project within the Pixel team, where responsibilities include designing data collection approaches, tuning models, and improving AI systems. Adobe, on the other hand, seeks ML engineers to design and deploy models, work in cross-functional teams, and mentor others to drive AI innovation.
Beyond these tech giants, a host of companies across industries are valuing ML engineers to transform their business challenges into ML-driven solutions. Startups like Movable Ink are hiring engineering employees who can work with ML technologies to support content personalization powered by automations. SmartBear is looking for machine learning engineers to build models, clean data sets, and enhance testing tools with AI. Hinge is hiring machine learning engineers to ensure efficient data workflows throughout the full ML lifecycle.
Finance companies like Upstart are leveraging AI-driven lending platforms to lead to fewer defaults, lower APRs, and higher approval rates. Upstart is also hiring machine learning engineers to work on its AI-driven lending platform that evaluates over 1,800 non-traditional credit risk variables. MongoDB is hiring machine learning engineers to work on its multi-cloud database platform and help get AI-powered applications to market faster.
In the e-commerce sector, Klaviyo is hiring machine learning engineers to automate marketing workflows and send targeted messages across various channels. Roblox is hiring machine learning engineers to optimize models for GPU performance and analyze ML pipelines for bottlenecks.
Attain is hiring machine learning engineers proficient with Python to work on its opt-in purchase platform and provide marketers with comprehensive consumer intelligence. Airwallex is looking for machine learning engineers to capture generative AI opportunities and streamline its platform. Air Space Intelligence is hiring machine learning engineers to design systems for processing data streams and delivering real-time insights for mission-critical aviation and logistics operations.
Moreover, Hedra is hiring machine learning engineers to build and manage infrastructure and services for its video models. Movable Ink offers digital solutions for personal loans, auto refinance loans, small-dollar loans, and home equity lines of credit.
The roles and responsibilities of machine learning engineers broadly encompass the entire lifecycle of ML models, from data handling to deployment and ongoing maintenance. Key duties include data collection and preprocessing, model development and training, model deployment, monitoring and maintenance, optimization and scaling, collaboration and communication, lifecycle and version management, and mentoring and leadership in some roles.
Applied machine learning engineers specifically focus on delivering measurable business impact through ML models, often working with platforms like SageMaker, Vertex AI, or Databricks, and emphasizing practical use cases such as personalization, recommendation, fraud detection, or forecasting.
In summary, machine learning engineers are in high demand across various industries, and tech companies like Google and Adobe are prominent employers in this field today. These professionals bridge the gap between data science and production systems, ensuring that ML models are not only accurate but also robust, scalable, and aligned with business goals.
Machine learning engineers are being recruited by companies such as Hinge and MongoDB to ensure efficient data workflows and faster AI-powered applications in the business sector. In finance, Upstart is hiring machine learning engineers to work on its AI-driven lending platform, aiming to minimize defaults and improve approval rates. Attain seeks machine learning engineers proficient with Python to provide marketers with comprehensive consumer intelligence. The e-commerce sector is also utilizing machine learning engineers, with Klaviyo hiring them to automate marketing workflows and target messages, and Roblox hiring them to optimize models and analyze ML pipelines. Further, Air Space Intelligence is hiring machine learning engineers for mission-critical aviation and logistics operations that require real-time insights from data streams. In addition to these roles, machine learning engineers are expected to handle the entire lifecycle of ML models, from data handling to deployment and maintenance, with key duties including data collection, model development, optimization, and collaboration.
