mlops engineer

Clariti Cloud Inc.

<div><div>Join our mission to provide governments with exceptional experiences so they can do the same for their communities!
<h1 class="jobSectionHeader">
What do we do?</h1>

We empower governments to deliver exceptional citizen experiences.

Check out our 'About Us' page for a deep dive into our product and what makes us exceptional.</div>
How will you help us make an impact? &zwj;&zwj;

The Senior MLOps Engineer will design, build, and scale the systems that power CivCheck and Clariti's AI capabilities. As the first MLOps Engineer, you will lead the development of robust ML infrastructure, ensuring that models move efficiently from research to production with reliability, observability, and performance at scale.This role is ideal for someone who thrives at the intersection of machine learning, software engineering, and cloud infrastructure, and who's motivated to enable teams to deliver high-impact ML systems efficiently and safely.

As a X at Clariti, you'll get to :
<ul>
<li>Design and maintain end-to-end ML pipelines for training, evaluation, and deployment of models and agentic AI workflows</li>
<li>Build and optimize infrastructure for distributed training and model serving across GPU and cloud environments.</li>
<li>Develop tools for data creation, model versioning, experiment &amp; performance tracking, and automated retraining.</li>
<li>Collaborate with AI researchers and ML engineers to productionize POCs and ensure model reproducibility and scalability.</li>
<li>Implement CI/CD best practices for ML systems, including continuous integration, automated testing, and deployment workflows.</li>
<li>Monitor and manage model health, performance, drift, and data quality in production.</li>
<li>Partner with Engineering teams to streamline infrastructure provisioning and data access.</li>
<li>Drive cost optimization and performance tuning for large-scale model training.</li>
<li>Contribute to internal documentation and best practices.</li>
</ul>
What do you bring to the team?
<ul>
<li>6&ndash;10+ years of experience in software or ML engineering, with at least 3+ in MLOps or ML infrastructure.</li>
<li>Solid experience working with Python, C, C++, Bash, etc.</li>
<li>Proven experience deploying and managing ML models in production.</li>
<li>Proficiency with Docker, and Kubernetes for scalable ML system design.</li>
<li>Experience with cloud platforms (AWS, GCP, or Azure) and GPU orchestration.</li>
<li>Hands-on knowledge of CI/CD pipelines (GitHub Actions, Jenkins, or similar). 
Familiarity with MLflow, Weights &amp; Biases, Kubeflow, and other similar tools for experiment tracking and pipeline automation.</li>
<li>Solid understanding of data versioning, model reproducibility, and monitoring strategies.</li>
<li>Excellent problem-solving skills and a collaborative, team-oriented mindset.</li>
</ul>
Bonus Points
<ul>
<li>Experience training models from scratch, including defining architectures, curating &amp; cleaning datasets, tuning training parameters, and bringing models from research to monitored production.</li>
<li>Exposure to model optimization techniques (quantization, distillation, TensorRT, ONNX).</li>
<li>Familiarity with infrastructure-as-code tools (Terraform, CloudFormation).</li>
<li>Background in distributed systems or high-performance computing.</li>
<li>Contributions to open-source projects</li>
</ul>
What's in it for you?

We invest in and empower our team members with competitive compensation packages, well deserved time off and benefits to keep you and your family healthy! *

 The base salary range for this role is expected to be between $190,000-240,000 based on the candidate's skills, experience, and qualifications while considering internal pay equity and our broader pay philosophy.

If you have questions about compensation as we move through the process, we're happy to discuss further.
<ul><li>Benefits depend on employment type (full-time, part-time, contract, etc).</li></ul><div><h1 class="jobSectionHeader"> 
Things to Note</h1>

Background checks - Because our customers trust us with sensitive information, we require all successful candidates to undergo comprehensive background checks before joining our team. We focus strictly on global sanctions and criminal offences that are directly relevant to employment at Clariti, and follow all applicable privacy and human rights legislation.

Travel- Although we operate as a remote company, all roles are expected to participate in occasional travel for in-person company-wide or departmental meetings, typically 1-2 times per year. Additional travel requirements specific to the role, if any, will be outlined in the job description.

We're committed to building an inclusive culture where our team members take ownership over projects, tasks, and outcomes; bring a growth mindset to drive continuous learning and self-development; have the ability to communicate courageously in a direct but respectful way; and are customer-focused by keeping the customer at the heart of decision-making. It's the diversity of our team that helps us make better decisions, by leveraging the diversity in thought &amp; experience across to create impactful solutions as we explore new paths &amp; challenges as we grow. We're working to create a workplace and team that is as diverse as the communities we serve. We welcome and encourage candidates of all backgrounds to apply.
<h1 class="jobSectionHeader">
Questions? We are here to help</h1>

If you require accommodations in completing an application, interviewing, completing any pre-employment testing, or otherwise participating in our hiring process for any reason, please direct your questions to hr@claritisoftware.com and we'll be happy to support you.</div></div>

Senior MLOps Engineer

Zoolatech

<div><div><div><div><div><div><div><div>OVERVIEW</div>
</div><div><div>RESPONSIBILITIES</div>
</div><div><div>REQUIREMENTS</div>
</div></div></div></div><div><div><div>Are you passionate about improving the way Machine Learning systems are developed, deployed, and scaled in real-world production environments? We are collaborating with a leading European Online Fashion &amp; Beauty Retailer to find a highly capable and self-driven Machine Learning Engineer (MLE/MLOps Focus) to join a fast-moving and impactful team working on the Home page.
This role is centered around building robust ML workflows, streamlining feature creation, and standardizing ML components to ensure scalability, consistency, and speed across the organization. You&rsquo;ll work at the intersection of engineering and data science, playing a key part in shaping how machine learning is delivered at scale.
</div><div><ul><li>Design and build ML components, including systems for data access, feature management, model training, deployment, and inference at scale.</li><li>
Develop infrastructure and tooling that enable ML practitioners to experiment, version, deploy, and monitor models in a reliable and automated way.</li><li>
Architect scalable, modular, and reusable systems that serve as the backbone of ML development across multiple teams.</li><li>
Implement core abstractions and APIs &mdash; from feature creation to model rollout.</li><li>
Build and maintain observability and reliability tooling for ML systems &mdash; including telemetry pipelines, model health checks, and automated retraining triggers.</li><li>
Establish best practices, frameworks, and reference implementations that raise the bar for engineering rigor and speed in ML delivery.</li><li>
Work closely with infrastructure, data, and security teams to ensure that ML systems are secure, compliant, and production-grade by default.</li></ul>
</div><div><ul><li>5+ years of experience in Machine Learning Engineering or MLOps roles</li><li>
Solid Python development skills</li><li>
Strong hands-on experience with Airflow (MWAA), MLFlow, and/or SageMaker</li><li>
Familiarity with ML observability tools such as Grafana, custom metric logging, model drift detection, and alerting mechanisms</li><li>
Proficiency in building CI/CD pipelines for ML systems with automated testing and validation</li><li>
Experience with Infrastructure-as-Code tools (CloudFormation, YAML)</li><li>
Understanding of secure and compliant deployment of ML pipelines</li><li>
Excellent debugging and problem-solving skills</li><li>
Experience with OpenAI API usage in production, containerization, and Kubernetes orchestration is highly valued</li></ul>
</div></div></div><div><div><div><div>Location:
<div>Istanbul, Turkey
</div></div><div>Seniority:
<div>Senior
</div></div><div>Technologies:
<div>Python
</div></div></div></div><div><div>Benefits:
<ul><li>Paid Vacation
</li><li>Hybrid Work (home/office)
</li><li>Sick Days
</li><li>Sport/Insurance Compensation
</li><li>Holidays Day Off
</li><li>English Classes
</li><li>Training Compensation
</li><li>Transportation compensation</li></ul></div></div></div></div></div></div>

EPAM Systems

<div>We are looking for a Senior MLOps Engineer with expertise in Python and cloud technologies.
You will use your skills to build and maintain automation pipelines and improve system architecture. Join us to contribute to innovative projects and advance your career in a supportive environment.
Responsibilities<ul><li>
Develop and maintain automation pipelines on cloud or on-premise environments</li><li>
Apply prompt engineering techniques to optimize machine learning workflows</li><li>
Write Python code with comprehensive error handling and testing</li><li>
Implement DevOps practices for cloud and on-premise deployments</li><li>
Utilize engineering tools such as GitHub and CI/CD systems to ensure code quality</li><li>
Troubleshoot dependencies and enforce code standards including PEP 8 guidelines</li><li>
Design and improve system architecture to support scalable solutions</li></ul>
Requirements<ul><li>
Extensive experience in machine learning engineering with Python coding, minimum 3 years</li><li>
Proven background in MLOps implementation on cloud platforms</li><li>
Demonstrated DevOps experience in cloud or on-premise settings</li><li>
Proficiency in cloud services, especially Azure OpenAI Service</li><li>
Strong knowledge of engineering tools including GitHub and CI/CD pipelines</li><li>
Understanding of prompt engineering techniques</li><li>
Advanced English language proficiency</li></ul>
We offer<ul><li>
CONTINUOUS UPSKILLING, LEARNING &amp; DEVELOPMENT<ul><li>
Diversity of tasks and projects</li><li>
Assessment center for objective review of competency level</li><li>
Personal development plan</li><li>
Mentoring programs and leadership development</li><li>
Certification and professional development support</li><li>
Access to learning platforms including more than 2,500 internal courses and the LinkedIn Learning library with 20,000+ courses</li><li>
English courses taught by certified teachers</li></ul></li><li>
CORPORATE BENEFITS<ul><li>
Extra leave days</li><li>
Referral bonuses</li></ul></li><li>
COMPENSATION PACKAGE<ul><li>
Competitive compensation paid in USD</li><li>
Regular salary and performance reviews</li></ul></li><li>
MEDICAL &amp; HEALTHCARE<ul><li>
Private health insurance</li><li>
Well-being events</li></ul></li><li>
WORKING ENVIRONMENT<ul><li>
Recreation areas and kitchens</li><li>
Tea, coffee, and snacks</li><li>
Well-being events</li><li>
Sports equipment and game consoles</li><li>
IT Equipment</li><li>
Microsoft's Software Assurance Home Use Program (HUP)</li></ul></li></ul>
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.</div>

Senior MLOps Engineer with Python

W2S Solutions

Role: Junior ML Ops EngineerWork Mode: Onsite/Full timeLocation: Chennai, SholinganallurYear of Experience: 3 - 5 years Notice Period: Immediate or 15 daysGood To Have Skills: Good communicationMust Have Skills: Azure, MLOPS, Open AI/Generative AI, Continuous integration (CI) and continuous delivery (CD), PythonExternal Description:<ul><li>We are seeking a passionate and skilled Junior MLOps Engineer with 2-3 years of professional experience to join our team. In this role, you will collaborate closely with Data Scientists to migrate AI applications from Landing Zone V1 to Landing Zone V2 within the Azure Saint-Gobain private network.</li><li>The ideal candidate will possess a strong foundation in Python development, experience deploying applications on Azure, and familiarity with modern DevOps tools and practices. Your contributions will involve adapting Python code, conducting non-regression testing, and ensuring the seamless migration of AI applications.</li><li>3+ years of experience as an MLOps Engineer, Strong foundation in Python development for AI/ML applications.</li><li>Hands-on experience with Azure cloud services and deploying applications in secure environments.</li><li>Familiarity with DevOps tools and practices</li></ul>Interested candidates can reach us at @7338773388 or careers@w2ssolutions.com, &amp; hr@way2smile.comJob Types: Full-time, PermanentPay: &#8377;500,000.00 - &#8377;800,000.00 per yearWork Location: In person

Junior ML Ops Engineer

Deltacubes Technologies

Senior ML Platform Engineer (MLE and MLOps)Experience: 6-10 YearsLocation: Remote (Need local candidate from Noida or Bangalore)Employment Type: ContractJob OverviewWe are looking for a Senior ML Platform Engineer with strong expertise in Machine Learning Engineering and MLOps to join our dynamic team. The candidate should have a solid background in deploying production-grade ML/DL models and building scalable MLOps pipelines. Remote work is allowed, but candidates must be based in or around Noida or Bangalore. A LinkedIn profile is mandatory for application and vetting.Key ResponsibilitiesModel Packaging &amp; Serving: Containerize and optimize models (ONNX/TorchScript) for batch and real-time inference using Azure ML, Vertex AI, AKS/GKE, or TF Serving/TorchServe/Triton. Implement rollout strategies (A/B, canary, shadow, blue/green) with rollback controls.Pipelines &amp; Reproducibility: Develop reusable training and inference pipelines with Azure ML Pipelines, Vertex AI Pipelines, or Kubeflow. Enforce reproducibility via MLflow (tracking/registry) and DVC (dataset versioning).Features &amp; Data: Manage feature stores (Feast/Tecton) across ADLS/GCS, Synapse/BigQuery. Collaborate with Data Engineering on scalable ETL/ELT using ADF, Dataflow, and Databricks/Spark/Ray.Observability &amp; Reliability: Instrument services with Prometheus, Grafana, and OpenTelemetry; define SLOs for latency and throughput. Monitor drift, bias, and performance using Evidently, WhyLabs, or Arize with alerting and runbooks.CI/CD &amp; Automation: Implement CI/CD for code, data, and models using GitHub Actions, Azure DevOps, or Cloud Build. Automate infrastructure with Terraform/IaC and enforce policy-as-code.Security &amp; Compliance: Manage IAM/RBAC, secrets (Key Vault, Secret Manager), artifact signing, and PII controls; maintain audit trails.Activation &amp; Integration: Deliver predictions to Salesforce/Gainsight via APIs or connectors; enable reverse-ETL and event-driven workflows. Publish curated outputs to BI semantic layers (Power BI, Looker, Tableau).Cost &amp; Performance: Optimize compute (CPU/GPU), autoscaling, and caching; track cost per 1K predictions and batch efficiency.Required Skills6&ndash;10+ years in ML Engineering, MLOps, or Platform Engineering with multiple production services shippedProficiency in Python (FastAPI/Flask), SQL, PyTorch, TensorFlow, Bash, GitExperience with Azure ML, Vertex AI, Kubeflow, TorchServe, TF Serving, Triton, ONNX, TorchScriptSkilled in data and distributed computing using Spark, Ray, Databricks, BigQuery, SynapseExpertise in MLflow, DVC, Feast, Tecton for tracking, versioning, and feature storesCloud and orchestrations skills with AKS, GKE, Docker, Kubernetes, Azure Data Factory, GCP DataflowStrong CI/CD and IaC knowledge with GitHub Actions, Azure DevOps, Terraform, HelmFamiliarity with Prometheus, Grafana, OpenTelemetry, ELK stacks for monitoring and observabilityExperience with API integrations and reverse ETL workflowsJob Type: Contractual / Temporary Contract length: 6 monthsPay: &#8377;100,000.00 - &#8377;120,000.00 per monthWork Location: Remote

Senior ML Platform Engineer (MLE and MLops)

Labham PPPB Infrareality

We are looking for a highly skilled AI/ML Engineer with deep expertise in Microsoft Azure and Generative AI (GenAI) technologies. This role involves designing, developing, and deploying cutting-edge AI solutions using LLMs, RAG systems, and MLOps best practices, all within the Microsoft ecosystem.The ideal candidate will have hands-on experience with LangChain, LangGraph, Azure Machine Learning, and vector databases, and will play a pivotal role in building scalable, secure, and production-grade AI systems.Key Responsibilities:<ul><li>Design, develop, and deploy AI/ML models using Python, Azure Machine Learning, and Generative AI frameworks.</li><li>Build LLM-powered applications using tools like LangChain, LangGraph, FAISS, and Pinecone.</li><li>Implement and maintain RAG (Retrieval-Augmented Generation) workflows in production environments.</li><li>Integrate AI solutions with Azure services such as Functions, Data Lake, Synapse, and Cognitive Services.</li><li>Apply MLOps principles using Azure DevOps, Docker, and CI/CD pipelines for robust model lifecycle management.</li><li>Monitor and optimize model performance ensuring accuracy, scalability, and reliability.</li><li>Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders.</li><li>Ensure adherence to security, compliance, and governance in all AI solution deployments.</li><li>Stay updated on the latest in Azure AI, Generative AI, and machine learning trends.</li></ul>Required Qualifications &amp; Skills:<ul><li>Bachelor's or Master&rsquo;s degree in Computer Science, AI/ML, Data Science, or related field.</li><li>5+ years of hands-on experience in AI/ML model development using Python.</li><li>Experience with Large Language Models (LLMs) like GPT, Gemini, or similar.</li><li>1+ years of experience with Generative AI and RAG-based systems in production.</li><li>Proficiency with LangChain, LangGraph, and vector DBs (FAISS, Pinecone).</li><li>Solid understanding of deep learning and NLP architectures (Transformers, CNNs, RNNs).</li><li>Practical knowledge of PyTorch, TensorFlow, Keras, Scikit-learn, Pandas, and NumPy.</li><li>Experience with Azure AI stack (Azure ML, Azure Functions, Azure DevOps).</li><li>Familiarity with Docker, REST APIs, and CI/CD pipelines.</li><li>Excellent problem-solving, analytical, and communication skills.</li></ul>Preferred / Nice-to-Have:<ul><li>Azure Certifications &ndash; Azure AI Engineer Associate or Azure Data Scientist Associate.</li><li>Experience with MLOps frameworks and model lifecycle management.</li><li>Knowledge of healthcare data standards (e.g., X12, HL7).</li><li>Familiarity with Power BI or other Microsoft analytics tools.</li></ul>Job Types: Full-time, Contractual / Temporary Contract length: 12 monthsPay: &#8377;100,000.00 - &#8377;120,000.00 per monthBenefits:<ul><li>Work from home</li></ul>Work Location: Remote

AI/ML Engineer – Azure & GenAI

Infosys

<div><h2 class="jobSectionHeader">Job Description:</h2> 
<ul>
<li>Infosys is seeking a ML Engineer with strong background in designing and deploying machine learning models using MLOPS framework for Model Management</li>
<li>Ideal candidate will work with clients to understand the issues they face diagnose problems design solutions and facilitate solution deployment on Azure ML</li>
<li>One will also have the opportunity to shape value adding consulting solutions for clients by connecting various functions of cloud components</li>
<li>Ideally the candidate uses understanding of the problem to arrive at multiple solution alternatives keeping in mind the various stakeholders and assess the pros and cons of all the alternatives to arrive at the optimal solution</li>
<li>Required Qualifications</li>
<li>Bachelor s degree or foreign equivalent required from an accredited institution</li>
<li>Will also consider three years of progressive experience in the specialty in lieu of every year of education</li>
<li>At least 7 years of experience in Information Technology</li>
<li>All applicants authorized to work in the United States are encouraged to apply</li>
<li>Candidate must live within commuting distance of Indianapolis IN or be willing to relocate</li>
<li>Travel within the US may be required</li>
<li>At least 4 years of experience in Information Technology in MLOPS</li>
<li>At least 4 years of experience Python Programming for ML Model deployment with Cleancode standards</li>
<li>At least 4 years of experience in AZURE or GCP Cloud environment</li>
<li>Azure Certified DP100 AZ AI900 or GCP equivalent including DevOps certification</li>
<li>Professional experience setting up MLOPs Framework ML CI CD pipelines Model management monitoring and Refactoring of MLOPs runs</li>
<li>At least 2 years of implementation experience in DevOps MLOps tools like Grafana Prometheus Poetry Snyk and others or equivalent in other environments</li>
<li>At least 2 years of experience in MLOPS Framework industry standards and operations KPI</li></ul> 
<h2 class="jobSectionHeader">
Key Responsibilities:</h2> 
<ul>
<li>Roles Responsibilities</li>
<li>Understand the requirements from the business and translate it into an appropriate technical requirement</li>
<li>Responsible for successful delivery of MLOps solutions and services in client consulting environments</li>
<li>Define key business problems to be solved formulate high level solution approaches and identify data to solve those problems develop analyze draw conclusions and present to client</li>
<li>Assist clients with operationalization metrics to track performance of ML Models</li>
<li>Help team with ML Pipelines from creation to execution</li>
<li>Guide team to debug on issues with pipeline failures</li>
<li>Understand and take requirements on Operationalization of ML Models from Data Scientist</li>
<li>Engage with Business Stakeholders with status update on progress of development and issue fix</li>
<li>Setup Standards related to Coding Pipelines and Documentation</li>
<li>Research on new topics services and enhancements in Cloud Technologies</li></ul> 
<h2 class="jobSectionHeader">
Technical Requirements:</h2> 
<ul>
<li>Preferred Qualifications</li>
<li>Experienced in Agile way of working manage team effort and track through JIRA</li>
<li>High Impact client communication</li>
<li>Domain experience in Retail CPG and Logistics</li>
<li>Experience in Test Driven Development and experience in using Pytest frameworks git version control Rest APIs</li>
<li>The job may entail extensive travel</li>
<li>The job may also entail sitting as well as working at a computer for extended periods of time</li>
<li>Candidates should be able to effectively communicate by telephone email and face to face</li></ul> 
<h2 class="jobSectionHeader">
Additional Responsibilities:</h2> 
<ul>
<li>EEO About Us</li>
<li>About Us</li>
<li>Infosys is a global leader in next generation digital services and consulting</li>
<li>We enable clients in more than 50 countries to navigate their digital transformation</li>
<li>With over four decades of experience in managing the systems and workings of global enterprises we expertly steer our clients through their digital journey</li>
<li>We do it by enabling the enterprise with an AI powered core that helps prioritize the execution of change</li>
<li>We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight</li>
<li>Our always on learning agenda drives their continuous improvement through building and transferring digital skills expertise and ideas from our innovation ecosystem</li>
<li>Infosys provides equal employment opportunities to applicants and employees without regard to race color sex gender identity sexual orientation religious practices and observances national origin pregnancy childbirth or related medical conditions status as a protected veteran or spouse family member of a protected veteran or disability</li></ul> 
<h2 class="jobSectionHeader">
Preferred Skills:</h2>
Technology-&gt;Machine learning-&gt;data science</div>

Machine Learning Engineer

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