{"id":1435891,"url":"https://alion.io/job/varite-data-engineer-ml-pipelines-remote","title":"Data Engineer (ML Pipelines) | Remote","company":{"id":3800635,"name":"VARITE","domain":"varite.com","url":"https://alion.io/company/varite","size_band":"5000+","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":1500000,"max":1800000,"currency":"INR","period":"year","gross":null,"usd_annual":18932},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"IAM","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Spark","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-09-29T01:29:34Z","employer_posted_date":null,"last_verified_at":"2026-09-29T01:29:34Z","board_verified":false,"closed_at":null,"days_open":19,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":19},"description":"Job Title: Data Engineer II\nLocation: Gurgaon, HR\nExperience Required: 3-5 Years\nSalary Range: 15 to 18 LPA\nRole Type : Contract\nContract Duration: 4 Months (With Possible Extension)\n\nAbout The Job:\nCompany Name: VARITE India Private Limited\nAbout The Client:\nAn American technological research and consulting firm based in Stamford, Connecticut that conducts research on technology and shares this research through private consulting, executive programs, and conferences. Its clients include large corporations, government agencies, technology companies, and investment firms.\nThe Client serves over 12,000 organizations in over 100 countries with an employee strength of 15,000.\nAbout The Job:\nClient is seeking a talented and passionate MLOpsEngineer to join our growing team.\nResponsible for building Python- and Spark-based ML solutions that ensure the reliability, scalability, and efficiency of machine learning workloads in production.\nCollaborate closely with data scientists, data engineers, and software engineers to operationalize ML models and optimize MLOps workflows.\nLeverage expertise in Python, Spark, ML model inferencing, AWS, and cloud-native technologies to drive data-driven initiatives.\nEssential Job Functions:\nMLOpsInfrastructure & Automation:\nDesign, implement, and maintain scalable and reliable MLOpspipelines on AWS.\nAutomate ML model inferencing, deployment, monitoring, retraining, and maintenance workflows.\nBuild and maintain Infrastructure as Code (IaC) using Terraform or equivalent tools.\nImplement and manage CI/CD pipelines for API, ML model, and infrastructure deployments.\nEstablish automated testing, validation, versioning, and release processes for ML pipelines.\nImplement model and pipeline monitoring, logging, alerting, and operational dashboards.\nDevelop reusable automation frameworks and deployment patterns for machine learning workloads.\nDeployment & Scaling:\nDeploy pre-trained machine learning models on AWS using services such as SageMaker, EKS, and AWS Batch.\nOptimize model inference workloads for performance, scalability, availability, and cost efficiency.\nImplement batch and real-time model inference solutions based on business requirements.\nManage containerized ML workloads using Docker and Kubernetes.\nSupport model versioning, rollback, blue/green deployments, and controlled production releases.\nTroubleshoot model serving, deployment, networking, and infrastructure-related issues.\nDataEngineering & Management:\nDesign and implement data pipelines for ML inference using AWS services such as S3, EMR, Glue, and Athena.\nDevelop scalable data processing workflows using Apache Spark and Python.\nEnsure data quality, consistency, validation, and availability for ML pipelines.\nOptimize data storage, processing, and retrieval to improve ML inference performance.\nWork with structured and unstructured datasets and support large-scale data processing.\nImplement data lineage, pipeline monitoring, and error-handling mechanisms.\nCollaboration & Communication:\nCollaborate with data scientists and fellow engineers to ensure smooth model deployment and production operations.\nPartner with data engineering, DevOps, and cloud teams to establish scalable ML infrastructure.\nCommunicate technical concepts, implementation approaches, and findings effectively to technical and non-technical stakeholders.\nParticipate in code reviews and contribute to engineering standards and MLOps best practices.\nTroubleshoot and resolve production issues related to ML pipelines, model inference, applications, and infrastructure.\nDocument architecture, deployment procedures, operational processes, and troubleshooting guidelines.\nContinuously evaluate new MLOps technologies and recommend improvements to existing platforms and workflows.\nQualifications:Data Engineer:\nStrong proficiency in Python and Spark.\nExperience with AWS cloud services particularly Sagemaker, Lambda, EKS, S3, Glue, EMR and Terraform or other equivalent cloud (IAC).\nExperience with containerization technologies (e.g., Docker, Kubernetes).\nBachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field with 3-5 years of experience working with data and ML services using Python and Spark.\nStrong proficiency in Python and Apache Spark.\nHands-on experience with AWS cloud services, particularly SageMaker, Lambda, EKS, S3, Glue, EMR, and Athena.\nStrong experience with Terraform or equivalent Infrastructure as Code (IaC) technologies.\nExperience with Docker and Kubernetes and containerized application deployment.\nExperience developing and managing CI/CD pipelines for ML applications and infrastructure.\nStrong understanding of ML model deployment, model serving, and inference workflows.\nExposure to MLOpsplatforms, tools, and best practices.\nExposure to Big Data technologies and dataengineering concepts.\nUnderstanding of cloud security, IAM, networking, monitoring, and AWS best practices.\nExperience with REST APIs, serverless architectures, and event-driven workflows is an added advantage.\nStrong problem-solving, troubleshooting, and analytical skills.\nAbility to work effectively in a collaborative, cross-functional team environment.\nStrong understanding of software development lifecycle, version control, testing, and deployment practices.\nAbility to design reliable, scalable, and production-ready ML solutions.\n\nHow to Apply:Interested candidates are encouraged to respond/submit their updated resumes, and for additional job opportunities, please visitJobs In India VARITE.\nUnlock Rewards:Refer Candidates and Earn.\nIf you're not available or interested in this opportunity, please pass this along to anyone in your network who might be a good fit and interested in our open positions. VARITE offers a Candidate Referral program, where you'll receive a one-time referral bonus based on the following scale if the preferred candidate completes a three-month assignment with VARITE.\nExperience Level Bonus Referral:\n0-2 years INR 5,000\n2-6 years INR 7,500\n6+ years INR 10,000\nAbout VARITE:VARITE is a global staffing and IT consulting company providing technical consulting and team augmentation services to Fortune 500 Companies in USA, UK, CANADA and INDIA. VARITE is currently a primary and direct vendor to the leading corporations in the verticals of Networking, Cloud Infrastructure, Hardware and Software, Digital Marketing and Media Solutions, Clinical Diagnostics, Utilities, Gaming and Entertainment, and Financial Services.\nEqual Opportunity Employer:\nVARITE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, marital status, veteran status, or disability status","description_format":"text","description_chars":6859,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence"],"lifecycle":[{"event":"open","at":"2026-09-29T03:00:00Z"}],"visa":[],"liveness":{"score":24,"band":"cold","label":"Long shot","p_open":0.85,"p_active":0.515,"p_room":0.55,"age_days":18,"expected_fill_days":18,"reasons":["seen:18","agency","urgency","velocity","win:tail"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":18932,"is_top_pay":false},"html_url":"https://alion.io/job/varite-data-engineer-ml-pipelines-remote","json_url":"https://alion.io/job/varite-data-engineer-ml-pipelines-remote.json","meta":{"generated_at":"2026-10-18T04:06:14Z","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":6262,"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":3800635},"rest":"https://alion.io/mcp/rest/get_company?id=3800635"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fvarite-data-engineer-ml-pipelines-remote"},{"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%2Fvarite-data-engineer-ml-pipelines-remote"},{"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%2Fvarite-data-engineer-ml-pipelines-remote"},{"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/varite-data-engineer-ml-pipelines-remote\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fvarite-data-engineer-ml-pipelines-remote"}]}