Top Machine Learning Jobs in Ankara

The Senior Project Manager will lead engagements for Google Cloud adoption, managing diverse teams and stakeholders while delivering projects effectively and mitigating risks.

The Machine Learning Engineer will develop machine learning models and pipelines, research linguistic characteristics, engineer prompts for LLMs, and collaborate with teams to integrate AI/ML features into Smartling's platform, ensuring high-quality features for clients.

As a Senior L2 Support Engineer, you will resolve complex technical issues, mentor junior staff, lead troubleshooting, and improve operational efficiency through scripting and collaboration.

As a Senior ML Engineer at Smartcat, you will enhance translation capabilities by optimizing machine learning models and managing the full lifecycle of ML projects. Responsibilities include developing benchmarks, improving translation quality, and automating systems while leveraging advanced technologies and cloud infrastructure.

Edge Impulse seeks candidates interested in remote roles, promoting AI and machine learning model development for edge hardware. Applicants are encouraged to apply, even if no specific role aligns with their skills.

As a Senior ML Engineer, you will develop and deploy ML features for a CRM platform, collaborate with teams, and improve existing systems while iterating on user feedback.

The Senior Data Consultant leads teams to deliver data-driven projects for clients, formulating strategies and action plans, managing project delivery, and building customer relationships. They are problem solvers and project managers, skilled in adapting to diverse missions and leveraging data to drive business impact.

As a Refining and Petrochemical Process Optimization Engineer, you will apply machine learning and process engineering to optimize industrial processes. Responsibilities include collaborating with clients, evaluating machine learning models, developing product usage insights, and training clients on technology usage, all while traveling throughout Europe.

As a Senior AI/ML Engineer at Nansen, you will develop and monitor AI models to analyze blockchain data, collaborate with cross-functional teams to enhance the platform's analytical capabilities, and mentor junior engineers. Your work will significantly influence decision-making for crypto investors and drive the technology forward.

Lead the development and deployment of machine learning models, manage a team of data scientists, collaborate across departments, and ensure alignment with business objectives.

The AI/ML Specialist Solutions Architect designs AI solutions for clients, resolves technical challenges, and manages scalable AI deployments.

As a Computer Vision / Machine Learning Engineer, you will enhance Scan-to-CAD automation leveraging a unique dataset of scans and CAD models. Your responsibilities include researching state-of-the-art approaches, developing algorithms, training neural networks, automating internal tooling, and improving ML infrastructure.

As a Data Platform Engineer, you will support the ML Platform Team in developing a high-scale compute and data platform, provision and expose data for researchers, implement workflow orchestrators, and ensure ML engineering best practices are followed.

As an Engineering Manager, you will lead multiple product teams to enhance vegetation modeling and data ingestion, manage up to 10 engineers, and ensure high-quality product delivery while fostering team growth and collaboration.

Develop and enhance Autodesk's AI/ML platform by leading system design, automation, and deployment processes. Collaborate cross-functionally to optimize workflows and implement scalable services, while leveraging big data and cloud technologies for efficiency and effectiveness.

The Senior Machine Learning Applied Scientist will apply reinforcement learning techniques to solve real-world marketing challenges, improve algorithms, conduct research, and collaborate with engineering teams to enhance the platform and develop APIs. The role involves using advanced evaluation methods and monitoring tools, engaging with customer implementations, and contributing to product strategy.