{"id":2112874,"url":"https://alion.io/job/square-one-resources-machine-learning-engineer-data-scientist-geospatial-data","title":"Machine Learning Engineer / Data Scientist – Geospatial Data","company":{"id":3913592,"name":"Square One Resources","domain":"squareoneresources.com","url":"https://alion.io/company/square-one-resources","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Traffit","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"contractor","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":250,"max":300,"currency":"PLN","period":"hour","gross":null,"usd_annual":154000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Keras","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"NumPy","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false},{"name":"Scala","optional":true}],"status":"live","first_seen_at":"2026-09-17T09:34:43Z","employer_posted_date":null,"last_verified_at":"2026-09-17T09:34:43Z","board_verified":false,"closed_at":null,"days_open":25,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":25},"description":"Project DescriptionWe are looking for an experienced Machine Learning Engineer / Data Scientist to join a long-term project focused on improving the quality, accuracy, and reliability of large-scale geospatial datasets.In this role, you will design and develop machine learning systems, perform advanced data analysis, and build solutions for extracting structured information, detecting anomalies, and measuring data quality.You will work across the entire ML lifecycle — from experimentation and model development through integration and productionization to deployment at scale. The position combines machine learning and data science expertise with strong software engineering skills.The project offers an opportunity to work on complex, data-intensive challenges and contribute to solutions that operate on large-scale datasets.\nLocation: Malmö, Sweden\nWork model: Remote, with occasional on-site presence in Malmö\nRelocation: Relocation to Malmö is required for the duration of the projectZakres obowiązków\nDesign, develop, test, and deploy machine learning models\nDevelop solutions for large-scale geospatial data processing and quality improvement\nApply machine learning and data science techniques to identify patterns, generate insights, and detect anomalies\nPerform feature engineering and develop predictive and classification models\nWork with NLP and LLM-based solutions to extract and structure information from data\nDesign and implement prompting strategies and agent-based workflows\nBuild and maintain scalable data processing and software solutions\nTake ownership of ML features and improvements throughout the entire development lifecycle\nIntegrate machine learning models into existing production systems\nSupport model productionization, deployment, monitoring, and further improvement\nCollaborate with data scientists, software engineers, and other cross-functional stakeholders\nBalance experimentation and innovation with practical implementation within existing systems\nWymagania\nStrong programming skills, with extensive commercial experience in Python\nProven professional experience in Machine Learning and Data Science\nHands-on experience with ML techniques such as:classification\nclustering\nfeature engineering\nanomaly detection\nneural networks\n\nPractical experience working with LLMs, including prompting and agent-based workflows\nSolid understanding of classical machine learning algorithms, such as:Support Vector Machines (SVM)\nRandom Forest\nNaive Bayes\nk-Nearest Neighbors (k-NN)\n\nExperience with ML and data science libraries/frameworks, including PyTorch, TensorFlow, Keras, Scikit-learn, NumPy, and Pandas\nStrong analytical and problem-solving skills\nExperience taking ML solutions from experimentation to production\nAbility to work effectively with existing software and data systems\nStrong ownership mindset and ability to independently drive tasks to completion\nGood written and verbal communication skills\nAbility to work effectively in a fast-paced, collaborative environment\nWillingness to relocate to Malmö, Sweden for the duration of the project and be available for occasional on-site work\nNice to HaveCommercial experience with Scala or Java\nKnowledge of Natural Language Processing (NLP)\nExperience with Information Retrieval\nExperience in Data Mining\nBackground in statistical modelling\nExperience building predictive models\nExperience working with large-scale or geospatial datasets\nTech stack\nPython\nMachine learning\nData science\nLLMs\nSupport Vector Machines\nSVM\nRandom Forest\nNaive Bayes\nk-Nearest Neighbors (k-NN)\nPyTorch\nTensorFlow\nKeras\nscikit-learn\nNumPy\nPandas\nAnalytical skills\nProblem-Solving\nCommunication skills\nScala\nJava\nNatural language processing\nNLP\nInformation Retrieval\nData mining\nStatistical modelling\npredictive 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