Machine Learning Engineer (Applied ML) at Jobgether

, , Germany -

Full Time

Start Date

Immediate

Expiry Date

19 Jan, 26

Salary

0.0

Posted On

21 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Applied Research, Software Engineering, PyTorch, JAX, TensorFlow, Communication Skills, Ownership Mindset, Curiosity, Reinforcement Learning, Efficient ML Architectures

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Machine Learning Engineer (Applied ML) in United States, United Kingdom, Germany, France, Canada. This role offers the opportunity to work at the intersection of applied research and real-world AI products. You will lead the design, development, and deployment of adaptable and efficient machine learning systems that directly impact production environments. Collaborating closely with technical and strategic teams, you will translate complex challenges into actionable solutions while shaping both research directions and product strategies. The ideal candidate thrives in a fast-paced, innovative environment, balancing technical excellence with practical execution to deliver measurable results. Accountabilities: Lead the development and deployment of efficient, adaptive machine learning systems in production environments. Collaborate with strategic partners, acting as a trusted technical advisor and translating complex requirements into actionable solutions. Own the implementation of data products and ML systems, applying creativity and technical expertise to solve novel challenges. Contribute to research and product vision, providing insights that influence roadmap and strategic direction. Ensure alignment between technical execution and business goals, optimizing for real-world impact and efficiency. Bachelor’s degree (or higher) in Computer Science, Machine Learning, or a related field. 3–4 years of experience in machine learning, applied research, or systems-level AI engineering. Strong software engineering skills and proficiency with ML frameworks such as PyTorch, JAX, or TensorFlow. Excellent communication skills and ability to align technical solutions with business objectives. Ownership mindset, curiosity, and a bias toward action. Bonus: experience with online learning, reinforcement learning, or efficient ML architectures. Bonus: demonstrated track record of deploying ML systems that solved real business problems. Competitive salary with meaningful equity participation. Opportunity to shape both research and product strategy as part of the founding team. Work at the cutting edge of AI efficiency research, collaborating with world-class peers. Budget for learning, professional development, and certifications. Fully remote role, with flexibility across multiple geographies. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score. 🎯 Based on this analysis, we automatically shortlist the three candidates with the highest match to the role. 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias, focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team. Thank you for your interest! #LI-CL1

Responsibilities

Lead the design, development, and deployment of adaptable and efficient machine learning systems in production environments. Collaborate closely with technical and strategic teams to translate complex challenges into actionable solutions.