{"id":2290935,"url":"https://alion.io/job/sofascore-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":55703,"name":"SofaScore","domain":"sofascore.com","url":"https://alion.io/company/sofascore","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BambooHR","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"CI/CD","optional":false},{"name":"Computer Vision","optional":false},{"name":"Embeddings","optional":false},{"name":"Fine-tuning","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Reranking","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Sentiment Analysis","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Tokenization","optional":false}],"status":"live","first_seen_at":"2026-08-10T00:00:00Z","employer_posted_date":"2026-08-10","last_verified_at":"2026-10-18T04:48:12Z","board_verified":true,"closed_at":null,"days_open":69,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":69},"description":"ABOUT SOFASCORE\nSofascore is a sports-tech company created with one goal in mind - giving sports enthusiasts a deeper understanding of the game.\nOur platform is the leading provider of advanced sports insights. From the biggest derbies to amateur matches, every game counts - that’s why we have the largest data coverage with 20,000+ tournaments across 25 sports. This comes easy with Torneo, our very own tournament management software for lower leagues.\nThe global recognition of the Sofascore Rating, along with the Player of the Season award for the highest-rated players, positioned us as the authority in evaluating player performance.\nThe Sofascore team counts more than 300 experts in 20 teams, primarily playing at our home court in Croatia, but we also have talents showing their skills worldwide.\nMore about the company /// More about the platform\nABOUT THE ROLE\nAt Sofascore, we build products used by tens of millions of people worldwide, turning large volumes of sports and user data into meaningful experiences.\nWe are looking for a Machine Learning Engineerto join our AI Team and work on real-world ML problems across recommender systems and personalized feeds, semantic search, sentiment analysis, NLP, LLM-powered applications, and other machine learning use cases, potentially including computer vision.\nThis is an engineering-focused ML role. We are looking for someone who goes beyond experimenting with models in notebooks: someone who can take an ambiguous product or business problem, understand the data behind it, choose an appropriate approach, and turn it into a well-engineered ML solution.\nYou do not need to have worked on every type of problem we solve. What matters is a strong foundation in machine learning and software engineering, hands-on experience with modern ML and LLM systems, and the ability to think critically about which approach is appropriate for a given problem.\nYou will work on both new and existing ML systems and collaborate closely with engineers, analysts, and product teams. At Sofascore's scale, technical decisions have real consequences: scalability, latency, reliability, computational cost, and maintainability all matter alongside model quality.\nWe prefer candidates who are able to complete the onboarding process from our Zagreb office. Following successful completion of the onboarding process, the role can be performed fully remotely.\nYour Responsibilities\nDesign, develop, evaluate, and improve machine learning solutions for real product problems used by tens of millions of users worldwide\nWork on a broad range of ML use cases, including recommender systems, personalized feeds, semantic search, sentiment analysis, NLP, LLM-powered applications, classical machine learning problems, and potentially computer vision\nTake ownership of ML problems end-to-end: from understanding the business problem and exploring the data to selecting an approach, building and evaluating models, and collaborating on their integration into our systems\nDevelop new ML solutions while also improving and maintaining existing systems\nBuild LLM-powered solutions and contribute to the design of retrieval-augmented generation and other modern NLP systems\nWrite clean, maintainable, testable, production-quality Python code following sound software engineering practices\nWork with large datasets using Python and SQL, and build reliable data and model workflows\nEvaluate models rigorously, select meaningful metrics, identify issues such as overfitting and data leakage, and understand the trade-offs behind different modelling approaches\nCollaborate with product managers, analysts, software engineers, and other stakeholders to translate product and business needs into well-defined ML problems\nCritically evaluate proposed solutions and choose the right level of complexity for the problem, whether that means a simple heuristic, classical ML, deep learning, a recommender system, or an LLM-based approach\nStay current with developments in machine learning and LLMs, while applying new techniques where they provide meaningful value rather than complexity for its own sake\nWhat you bring to the team\n2+ years of professional industry experiencein a Machine Learning or closely related engineering role\nA Master's degreein Computer Science, Software Engineering, Mathematics, Electrical Engineering, Data Science, or another relevant technical or quantitative field\nStrong foundations in machine learning, including supervised and unsupervised learning, model selection, feature engineering, regularization, validation, hyperparameter optimization, and appropriate evaluation methodologies\nStrong understanding of modern deep learning methods and architectures, including transformers\nHands-on professional experience working with LLMs, combined with a solid understanding of how they work beyond the API level, including transformer architecture, attention, tokenization, context windows, inference, and fine-tuning approaches\nUnderstanding of RAG systemsand key concepts such as embeddings, retrieval, and evaluation\nStrong Python programming skills and the ability to write clean, maintainable, testable, production-quality code\nHands-on experience with modern ML frameworks and libraries such as PyTorch, scikit-learn, TensorFlow, or similar\nGood practical knowledge of SQLand experience independently working with large datasets\nPractical experience with Dockerand containerized development\nStrong analytical and critical-thinking skills: you should be comfortable challenging assumptions, identifying limitations in data or proposed approaches, and explaining why a particular solution is appropriate\nAbility to work independently on ML problems, make sound technical decisions, and take ownership from problem definition through implementation and evaluation\nStrong communication and collaboration skills and the ability to work effectively across engineering, analytics, and product teams\nWhat sets you apart\nYou do notneed to have all of the following. These are additional strengths that would make your experience particularly relevant to the problems we work on:\nExperience building recommender systems, ranking systems, or personalization solutions\nPractical experience designing and implementing RAG systems, including more advanced retrieval, reranking, or evaluation approaches\nExperience fine-tuning LLMs, working with open-source language models, optimizing inference, or serving models at scale\nExperience taking ML systems into production and working across the broader ML lifecycle, including training, experiment tracking, deployment, CI/CD, model serving, monitoring, and retraining\nExperience with Kubernetesand container orchestration\nExperience designing or operating large-scale, consumer-facing ML systems, particularly where scalability, latency, reliability, and computational cost are important engineering considerations\nExperience with cloud platforms and cloud-based ML infrastructure\nExperience with A/B testing or measuring the impact of ML models on real product and business metrics\nExperience with modern NLP methods beyond LLM applications or with computer vision\nExperience mentoring other engineers, sharing technical knowledge, or contributing to engineering standards\nResearch or applied innovation experience\nWhat we offer\nThe opportunity to work with a cutting-edge sports platform impacting millions worldwide\nFamily benefits package\nEducation - internal and through international conferences and workshops\nTop-quality equipment and budget for a mobile phone\nPaid package of general physical examination once a year\nSofascore Canteen (lunch options)\nSofascore Bar (coffee and drinks on us)\nNumerous other benefits that we would verbally communicate to you\nSounds good? It gets even better!\nSend us your CV in English.\nLooking forward to hearing from you. Let’s get the ball rolling!","description_format":"text","description_chars":7882,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-11T18:22:37Z"}],"visa":[],"liveness":{"score":8,"band":"cold","label":"Long shot","p_open":1,"p_active":0.293,"p_room":0.28,"age_days":68,"expected_fill_days":19,"reasons":["conf:3","win:tail","crowd:junior"],"computed_at":"2026-10-17T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/sofascore-machine-learning-engineer","json_url":"https://alion.io/job/sofascore-machine-learning-engineer.json","meta":{"generated_at":"2026-10-18T06:29:48Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":9591,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-19T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":55703},"rest":"https://alion.io/mcp/rest/get_company?id=55703"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fsofascore-machine-learning-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fsofascore-machine-learning-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fsofascore-machine-learning-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/sofascore-machine-learning-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fsofascore-machine-learning-engineer"}]}