{"id":1678041,"url":"https://alion.io/job/ups-senior-mle-python-ml-frameworks-mlops-containerization-terraform-gcp-vertex-ai-ibm-watsonx","title":"Senior – MLE – Python, ML Frameworks, MLOps, Containerization, Terraform, GCP, Vertex AI, IBM Watsonx","company":{"id":37664,"name":"UPS","domain":"ups.com","url":"https://alion.io/company/ups","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Phenom","truth_index":{"grade":"A","score":97,"open_postings":361,"ghost_share":0.055,"stale_share":0.044,"repost_share":0.227,"time_to_fill_p50_days":9,"computed_at":"2026-10-20T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19000,"max_usd":39000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":38},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Feature Store","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"Helm","optional":false},{"name":"Jenkins","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Kubeflow","optional":false},{"name":"Machine Learning","optional":false},{"name":"RAG","optional":false},{"name":"Terraform","optional":false},{"name":"Vertex AI","optional":false},{"name":"Amazon SageMaker","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"Evidently AI","optional":true},{"name":"Flink","optional":true},{"name":"GCP","optional":true},{"name":"Grafana","optional":true},{"name":"Hadoop","optional":true},{"name":"Interpretability","optional":true},{"name":"Kubernetes","optional":true},{"name":"LIME","optional":true},{"name":"Prometheus","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Scikit-learn","optional":true},{"name":"SHAP","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true},{"name":"TensorFlow","optional":true},{"name":"XGBoost","optional":true}],"status":"live","first_seen_at":"2026-08-15T00:00:00Z","employer_posted_date":"2026-10-02","last_verified_at":"2026-10-20T16:31:39Z","board_verified":true,"closed_at":null,"days_open":66,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":66},"description":"Before you apply to a job, select your language preference from the options available at the top right of this page.\nExplore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow-people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level.\nJob Description:\nAbout Machine Learning Engineering at UPS Technology:\nWe’re the obstacle overcomers, the problem get-arounders. From figuring it out to getting it done… our innovative culture demands “yes and how!” We are UPS. We are the United Problem Solvers.\nOur Machine Learning Engineering teams use their expertise in data science, software engineering, and AI to build next-generation intelligent systems. These systems power our Smart Logistics Network, optimize UPS Airlines, and enhance Global Transportation Operations. We build scalable, production-grade ML solutions that move up to 38 million packages a day (4.7 billion annually), delivering measurable impact across the enterprise.\nAbout this Role:\nWe are seeking passionate Senior Machine Learning Engineers to design, develop, and deploy ML models and pipelines that drive business outcomes. You’ll work closely with data scientists, software engineers, and product teams to build intelligent systems that are robust, scalable, and aligned with UPS’s strategic goals.\nYou will contribute across the full ML lifecycle-from data exploration and feature engineering to model training, evaluation, deployment, and monitoring. You’ll also help shape our MLOps practices and mentor junior engineers.\nKey Responsibilities:\nDesign, deploy, and maintain production-ready ML models and pipelines for real-world applications.\nBuild and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.\nImplement automated retraining, drift detection, and re-deployment of ML models.\nDevelop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.\nImplement model monitoring, observability, and alerting across accuracy, latency, and cost.\nIntegrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.\nEnsure pipelines are secure, compliant, and cost-optimized.\nDrive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance.\nMentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.\nStay current with the latest ML research and apply new tools pragmatically to production systems.\nCollaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.\nRequired Qualifications:\nEducation\nBachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus).\nExperience\n5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.\nStrong foundations in data structures, algorithms, and distributed systems.\n Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL.\nHands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).\nExperience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow).\nFamiliarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management.\nExperience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop).\nPractical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)\nStrong understanding of statistical methods, ML algorithms, and deep learning architectures.\nPreferred\nExperience with real-time inference systems or low-latency streaming platforms (e.g. Kafka Streams).\nHands-on with feature stores and enterprise ML platforms (IBM WatsonX, Vertex AI).\nKnowledge of model interpretability and fairness frameworks (SHAP, LIME, Fairlearn) and responsible AI principles.\nStrong understanding of data/model governance, lineage tracking, and compliance frameworks.\nContributions to open-source ML/MLOps libraries or strong participation in ML competitions (e.g., Kaggle, NeurIPS).\nDomain experience in Logistics, supply chain, or large-scale consumer platforms.\n Employee Type:\nPermanentUPS is committed to providing a workplace free of discrimination, harassment, and retaliation.","description_format":"text","description_chars":4687,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Logistics","Freight Forwarding","Customs Brokerage","Courier Services"],"lifecycle":[{"event":"open","at":"2026-10-02T08:58:30Z"},{"event":"close","at":"2026-10-08T22:11:52Z"},{"event":"reopen","at":"2026-10-09T02:21:17Z"},{"event":"close","at":"2026-10-10T10:46:45Z"},{"event":"reopen","at":"2026-10-10T13:41:14Z"},{"event":"close","at":"2026-10-11T06:09:52Z"},{"event":"reopen","at":"2026-10-11T10:31:26Z"},{"event":"close","at":"2026-10-13T19:46:59Z"},{"event":"reopen","at":"2026-10-13T19:52:03Z"},{"event":"close","at":"2026-10-14T20:06:01Z"},{"event":"reopen","at":"2026-10-15T00:05:20Z"}],"visa":[],"liveness":{"score":6,"band":"cold","label":"Long shot","p_open":1,"p_active":0.22,"p_room":0.28,"age_days":66,"expected_fill_days":9,"reasons":["conf:2","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-20T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/ups-senior-mle-python-ml-frameworks-mlops-containerization-terraform-gcp-vertex-ai-ibm-watsonx","json_url":"https://alion.io/job/ups-senior-mle-python-ml-frameworks-mlops-containerization-terraform-gcp-vertex-ai-ibm-watsonx.json","meta":{"generated_at":"2026-10-20T18:06:31Z","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":20702,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-21T00:00:00Z"}},"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":37664},"rest":"https://alion.io/mcp/rest/get_company?id=37664"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fups-senior-mle-python-ml-frameworks-mlops-containerization-terraform-gcp-vertex-ai-ibm-watsonx"},{"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%2Fups-senior-mle-python-ml-frameworks-mlops-containerization-terraform-gcp-vertex-ai-ibm-watsonx"},{"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%2Fups-senior-mle-python-ml-frameworks-mlops-containerization-terraform-gcp-vertex-ai-ibm-watsonx"},{"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/ups-senior-mle-python-ml-frameworks-mlops-containerization-terraform-gcp-vertex-ai-ibm-watsonx\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fups-senior-mle-python-ml-frameworks-mlops-containerization-terraform-gcp-vertex-ai-ibm-watsonx"}]}