Senior Enablement Engineer - AI / ML (Remote - Germany) at Jobgether

, , Germany -

Full Time

Start Date

Immediate

Expiry Date

02 Feb, 26

Salary

0.0

Posted On

04 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Natural Language Processing, Data Quality, Model Evaluation, MLOps, Large Language Models, Data Management, Analytical Skills, Collaboration, Software Engineering, Model Deployment, Experimentation, Research, Model Optimization, Cross-Functional Teams, AI Strategy

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Enablement Engineer - AI / ML in Germany. In this role, you will leverage your expertise in machine learning, particularly in Natural Language Processing (NLP), to design, develop, and deploy intelligent solutions that directly support business objectives. You will work closely with cross-functional teams to translate complex data into actionable insights and build scalable ML models that drive operational excellence. This position offers an opportunity to work on cutting-edge technologies, shape AI strategy, and influence the deployment of models in production. You will be empowered to research and experiment with new ML techniques, optimize model performance, and maintain awareness of industry trends. The role is ideal for individuals who enjoy combining software engineering with data science in a collaborative, innovative environment. Accountabilities: Develop and train machine learning models aligned with business objectives, with robust performance metrics. Ensure data quality through verification, cleaning, and exploration processes to support model reliability. Research and acquire external datasets for training and experimentation purposes. Define and implement effective validation strategies for model evaluation and monitoring. Deploy models into production environments, ensuring seamless integration and operational efficiency. Stay up-to-date with advancements in machine learning and NLP, applying new techniques where appropriate. Collaborate with cross-functional teams to understand requirements and translate them into ML solutions. Master’s degree in Machine Learning, Computer Science, or a related field, preferably with NLP specialization. Proven experience in designing, training, and fine-tuning machine learning models. Hands-on expertise with at least one major ML framework, ideally PyTorch. Familiarity with MLOps practices, including deployment and serving ML models. Strong understanding of Large Language Models (LLMs) and third-party AI services. Experience in data management, including cleaning, visualization, and quality assurance. Strong analytical skills, experimentation mindset, and ability to communicate results to stakeholders. Ability to work collaboratively in a global, cross-functional team and adapt to a fast-paced environment. Competitive salary and performance-based incentives. Flexible remote or hybrid work arrangements. Access to cutting-edge AI/ML tools and technologies. Opportunities for professional development, including conferences, workshops, and courses. Collaborative, international, and inclusive work environment. Equipment and resources to support remote work. Exposure to large-scale, impactful AI/ML projects in a global organization. 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

Develop and train machine learning models aligned with business objectives while ensuring data quality and model reliability. Collaborate with cross-functional teams to translate complex data into actionable insights and deploy models into production environments.