This position is posted by Jobgether on behalf of Testlio. We are currently looking for a Senior Machine Learning Scientist in EMEA.
This role is a hands-on, high-impact opportunity to design, develop, and scale advanced AI-powered data products. You will transform large, complex datasets into actionable insights that directly influence product quality, user experience, and business decisions. The position blends applied machine learning, deep learning, and statistical modeling with real-world business impact. You will collaborate closely with engineering and product teams to deliver production-ready ML solutions while contributing to the growth of the data science practice. This is ideal for a curious, creative, and technically skilled scientist who thrives in a remote, collaborative, and fast-paced environment.
Accountabilities
- Partner with engineering and product leaders to define, design, and deliver AI-powered data products.
- Explore, model, and analyze complex datasets using machine learning, deep learning, and statistical methods.
- Prototype, validate, and deploy models into production at scale, ensuring accuracy, fairness, and performance.
- Implement AI techniques such as NLP, predictive analytics, anomaly detection, recommendation systems, and custom model training.
- Translate raw model outputs into clear, actionable insights for customers and internal stakeholders.
- Continuously measure, evaluate, and improve model performance, robustness, and scalability.
- Contribute to building and maturing the data science practice, including tools, processes, and best practices.
Requirements
Technical Skills:
- Advanced degree (Master’s or PhD) in Computer Science, Data Science, Statistics, or a related field.
- 5+ years of experience applying machine learning and statistical modeling to real-world problems, ideally in SaaS or data-intensive environments.
- Strong Python skills and experience with ML frameworks such as PyTorch or TensorFlow.
- Hands-on experience with NLP, predictive modeling, recommendation systems, anomaly detection, and training models from scratch.
- Expertise in data wrangling, feature engineering, and handling large, complex datasets.
- Knowledge of LLMs and SLMs, including architecture, training, fine-tuning (LoRA, QLoRA, SFT), and deployment strategies.
- Experience deploying ML models into production and familiarity with MLOps.
- Proficiency with SQL, cloud platforms (AWS, Azure), and data visualization tools.
Human Skills:
- Curiosity, creativity, and eagerness to experiment with cutting-edge techniques.
- Ability to translate technical outputs into tangible business value.
- Strong collaboration skills and comfort working across teams.
- Adaptability to fast-changing priorities in a scaling environment.
- Mentorship mindset and willingness to share knowledge with teammates.
- Continuous learning and growth-oriented approach to AI/ML advancements.
Benefits
- Fully remote position within EMEA or APAC (excluding high-cost-of-living regions per company policy).
- Competitive compensation package, aligned with experience and market benchmarks.
- Flexible paid time off, including personal days, sick days, and national holidays.
- Stock options and participation in company growth.
- $300 annual learning stipend for personal and professional development.
- Opportunity to work with large-scale, high-impact datasets.
- Collaborative, inclusive, and purpose-driven team culture.
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 3 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!
Originally posted on Himalayas
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