{"id":1220817,"url":"https://alion.io/job/softeq-senior-i-mlcv-engineer","title":"Senior I ML/CV Engineer","company":{"id":62427,"name":"Softeq","domain":"softeq.com","url":"https://alion.io/company/softeq","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"ADP","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Vilnius, Lithuania"],"countries":["LT"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":55000,"max_usd":138000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1271},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Git","optional":false},{"name":"MLFlow","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Azure","optional":true}],"status":"live","first_seen_at":"2026-09-24T11:00:00Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-09-25T18:22:51Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Established in 1997, Softeq was built from the ground up to specialize in new product development and R&D, tackling the most difficult problems in the tech sphere. Now we've expanded to offer early-stage innovation and ideation plus digital transformation business consulting. Our superpower is to deliver all of this under one roof on a global scale. So let's get started and build a better future together!\nAs we're expecting to expand our team and launch new projects within the next 1-2 months, we're already accepting applications and starting the interview process for selected candidates. We'd love to hear from you - feel free to apply!\nWhat the role does here\nMoves predictive models from experiment into regular operation: delay and duration forecasting, congestion forecasting, cost estimation, anomaly detection;\nBuilds and maintains feature pipelines over the curated data layer, with a documented catalog of model inputs and their lineage;\nMakes training sets reproducible through table versioning and access to historical data states.\nRuns batch and near-real-time inference as platform jobs wired into the existing dependencies and schedules;\nPublishes models as endpoints for the application to consume, and watches latency and cost per call;\nOwns release discipline: versioning, retraining, rollback, promotion of models across environments;\nProvides quality monitoring, drift detection on inputs and outputs, input validation and explainability support.\nMust have\nProduction-grade Python and PySpark, and confident Spark SQL;\nDatabricks at development and operations depth: jobs and orchestration with dependencies, job clusters and cluster policies, portable project bundles, source control integration;\nUnity Catalog: grants on tables and models, lineage, environment separation through catalogs;\nWorking Delta Lake knowledge: table versions and time travel, change data feed, optimization, and how data layout affects feature read performance;\nMLflow: experiment tracking, model registry, version promotion, publishing models as endpoints;\nFeature storage and reuse, with consistent computation between training and inference;\nHands-on experience operating models in production: monitoring, drift, retraining, incidents, rollback;\nTime-series and forecasting methods;\nGit, CI/CD, containers, secure handling of secrets.\nNice to have\nBuilt-in platform monitoring for data and model quality;\nProduction ML on Azure and integration with cloud services;\nUnderstanding of the platform consumption model and cost tuning for recurring jobs;\nGeospatial features and route data;\nEnvironments where a model must be explainable to business owners and auditors;\nTransportation, logistics or supply chain.\nSofteq communicates only from @softeq.com email addresses. We never request payments or fees for any reason during hiring - including trainings or courses to be completed, equipment, onboarding, or background checks - and we will not ask for banking information, cryptocurrency or gift cards. If you receive a message from any other domain or requesting payment, do not respond and report it to ","description_format":"text","description_chars":3126,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Embedded Software & RTOS","Embedded & Electronics Design","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-09-25T11:53:57Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":2,"expected_fill_days":32,"reasons":["conf:35","velocity","win:early"],"computed_at":"2026-09-27T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/softeq-senior-i-mlcv-engineer","json_url":"https://alion.io/job/softeq-senior-i-mlcv-engineer.json","meta":{"generated_at":"2026-09-28T04:35:11Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2881,"day_limit":5000,"remaining_today":2119,"minute_limit":60,"resets_at":"2026-09-29T00:00:00Z"}}}