Staff Machine Learning Scientist (Applied AI, Remote)

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Machine Learning Scientist (Applied AI) in EMEA.

Join a global, fully remote team driving innovation at the intersection of machine learning and data intelligence. In this role, you'll architect and deploy advanced AI solutions that transform complex real-world datasets into powerful, actionable insights. Your work will directly shape the next generation of intelligent data products—enhancing product quality, user experience, and business decision-making for global clients. This position offers the opportunity to build from the ground up, experiment with emerging AI techniques, and make a measurable impact in a collaborative, fast-paced environment that values curiosity, creativity, and excellence.

Accountabilities:

• Partner with engineering and product teams to design, develop, and deploy AI-powered data products at scale
• Explore, model, and analyze complex datasets using advanced statistical, machine learning, and deep learning techniques
• Prototype, validate, and operationalize models for NLP, recommendation systems, anomaly detection, and predictive analytics
• Research and apply cutting-edge methods, including LLMs, fine-tuning (LoRA, QLoRA, SFT), and scalable inference strategies
• Translate technical results into clear, actionable business insights for non-technical stakeholders
• Continuously evaluate and enhance model accuracy, fairness, and robustness through experimentation and optimization
• Contribute to defining standards, best practices, and tools that strengthen the company's data science culture and capabilities
  
  
  

Requirements

• Master's or PhD in Computer Science, Data Science, Statistics, or a related field
• 10+ years of hands-on experience applying ML and statistical modeling to real-world data problems, ideally within SaaS or data-centric products
• Strong programming skills in Python, with deep expertise in frameworks such as PyTorch and TensorFlow
• Proven experience in NLP, predictive modeling, recommendation systems, anomaly detection, and MLOps deployment
• Proficiency in SQL, data visualization tools, and cloud environments (AWS or Azure)
• Advanced understanding of LLM and SLM architectures, training, and fine-tuning methods
• Excellent communication skills with the ability to translate technical outputs into clear business narratives
• A collaborative, curious, and growth-oriented mindset with a passion for experimentation and innovation
  
  
  

Benefits


Benefits:

• 100% remote position across select EMEA countries
• Flexible schedules and supportive remote-first culture
• Competitive salary and comprehensive total rewards package
• Equity options and annual learning stipend to support continuous growth
• Inclusive, diverse team environment with strong representation and belonging
• Opportunities to work with cutting-edge datasets and shape next-generation AI solutions
  
  

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!