Role Description This is a conversion-oriented internship designed for candidates aiming for a full-time ML engineering role. Depending on your profile and interests, you could be placed on one of two flagship tracks: - Track 1. AI for Financial Services: You'll work on Machine Learning solutions for one of the most data-rich industries in the world. Problems you might tackle include: - Prediction models - Document analysis with ML - Fine-tuning LLMs for conversational data interfaces - Extracting actionable insights from large-scale datasets - Track 2. Computer Vision for Pharma: You'll contribute to Computer Vision pipelines deployed in pharmaceutical environments, focusing on: - Object tracking - Behaviour understanding - Solving complex real-world problems with nothing but a camera and a well-trained model Both tracks involve close collaboration with senior engineers and direct exposure to enterprise clients. This is not a support role; you'll be expected to contribute from day one. Qualifications - Experience with training custom ML models using PyTorch and XGBoost - Familiarity with API development - Good understanding of relational databases and experience with querying and managing data - Knowledge of version control systems (e.g., Git) - B2+ English proficiency Requirements - Build Machine Learning models with financial data - Design, build, and maintain CRUD APIs to interact with users and serve the models - Deploy, monitor, and maintain applications in Azure and Snowflake Benefits - Compensation: €830 gross/month (€5,000 gross total over 6 months) - Contract type: Collaborazione Occasionale - High non-cash value (mentorship, fast promotion, relocation fully covered) - Duration: 6 months, with a 1-month trial period - Relocation bonus: €3,000 gross, paid in three instalments of €1,000 each to support your move to Milan - Monthly travel reimbursement: up to €370 Company Description We are a Machine Learning and Computer Vision startup founded in 2020, headquartered in Dublin, Ireland, with an AI Lab in Milan, Italy. Our expertise spans Machine Learning and Generative AI for financial services and Computer Vision for life sciences. At Gemmo AI, we build custom AI solutions that combine automation with human insight. - Machine Learning & Engineering: 14 people, including 4 Ph.D.s - Business & Strategy: 3 people - Leadership: 2 people A lean, technical-first team and we're growing. We're looking to add 5 new tech roles before the end of the year.

About Us Pearl is AI for professional services at global scale—combining advanced AI with verified human expertise to deliver help that’s accurate, accountable, and fast. Since 2003, our network has connected millions of customers with licensed professionals across 196 countries, making real expertise available anytime, anywhere. Our Values - Data driven: Data decides, not egos - Courageous: We take risks and challenge the status quo - Innovative: We're constantly learning, creating, and adapting - Lean: We focus on customers, using lean testing to learn how to serve them best - Humble: Past success is not a guarantee of future success About the Role As a Senior Software Engineer in our Machine Learning department, you will take ownership of high-impact initiatives that drive product quality, monetization, and user experience. You’ll apply your expertise in Python, data analysis, and modern AI tools to build, deploy, and optimize ML solutions end-to-end. This is a hands-on technical role that blends data science and engineering to deliver measurable business outcomes. You’ll collaborate closely with cross-functional stakeholders and contribute to evolving areas such as LLMs, Generative AI, and ML infrastructure. The role offers exposure to complex data challenges and the opportunity to shape JustAnswer’s AI-driven capabilities. What You’ll Do - Build, train, and deploy ML models that improve product performance and monetization. - Collaborate with data, product, and engineering teams across multiple internal initiatives. - Design and implement data pipelines for extraction, transformation, and analysis. - Apply statistical and machine learning techniques to real-world business problems. - Work on projects involving LLMs and Generative AI technologies. - Analyze large datasets to identify trends, insights, and optimization opportunities. - Integrate ML models into production systems and monitor their performance. - Communicate findings and recommendations clearly to technical and non-technical stakeholders. - Experiment with emerging AI tools and methodologies to enhance existing workflows. - Ensure data quality, reliability, and scalability in all deliverables. What We’re Looking For - 3+ years of hands-on experience in ML Engineering or Data Science. - 5+ years total experience in software or data engineering. - Strong programming skills in Python. - Proficiency in SQL for data querying and analysis. - Solid understanding of data processing, analysis, and visualization. - Experience with LLMs / Generative AI tools (e.g., OpenAI, Copilot, Cursor). - Ability to build and deploy ML models end-to-end. - Strong analytical and problem-solving mindset. - Experience with .NET for integration work - Upper-intermediate English proficiency (B2 or higher). - Familiarity with Databricks or similar data platforms (nice-to-have). - Exposure to AWS or other cloud-based ML environments (nice-to-have). Our Commitment to an Inclusive Workplace We welcome people from all backgrounds who seek the opportunity to help build a future where professional services are readily available to all. If you have curiosity, passion, and a collaborative spirit, come work with us. Pearl is committed to an inclusive workplace. Pearl is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. AI Disclosure & Informed Consent Artificial intelligence (AI) technology may be used during the hiring process to record, transcribe, analyze, and rank interview responses. By submitting your application and participating in the interview process, you acknowledge and consent to the use of AI technology in the hiring process. For more information see our AI Disclosure and Consent Policy. #LI-Remote

• Provide technical leadership and vision for large-scale distributed systems, ML platforms, and next-generation data infrastructure • Lead the design, architecture, and delivery of end-to-end solutions across the full SDLC, spanning development, testing, deployment, and operations • Drive innovation in Big Data, Generative AI, and Graph ML by translating emerging technologies into production-ready solutions • Architect scalable microservices and real-time inferencing systems leveraging modern ML infrastructure such as AI Agents, MCP, ML Inference, and LLM Gateway • Mentor and grow engineering teams, set technical direction, and foster a culture of engineering rigor, collaboration, and operational excellence • Champion best practices for building resilient, secure, and high-performance systems, optimized for scale and reliability

• Contribute to the design, build, evaluation, shipping, and refinement of systems that improve Spotify’s promotional performance with hands-on ML development • Collaborate with a multidisciplinary team to optimize machine learning models for production use cases, ensuring they are highly efficient, scalable, and consistently meet well-defined success criteria • Influence the technical design, architecture, and infrastructure decisions to support new and diverse machine learning architectures. • Work with Data and ML Engineers to support transitioning machine learning models from research and development into production • Implement and monitor model success metrics, diagnose issues, and contribute to an on-call schedule to maintain production stability.