ml ops engineer

Unify CX

<div>Job Title: ML Ops Engineer<br>
Location: Remote<br>
Department: Engineering<br>
Job Type: Full-time<br>
<br>
<b>Who We Are:</b><br>
unifyCX is an emerging Global Business Process Outsourcing company with a strong presence in the U.S., Colombia, Dominican Republic, India, Jamaica, Honduras, and the Philippines. We provide personalized contact centers, business processing, and technology outsourcing solutions to clients worldwide. In nearly two decades, unifyCX has grown from a small team to a global organization with staff members all over the world dedicated to supporting our international clientele.<br>
<br>
UnifyCX is a transformative AI platform that empowers and enables teams to deliver efficient, exceptional customer experiences. We engineer superhuman customer experiences through a powerful blend of strategy, omnichannel support, analytics, and AI-driven tools like GoTalent.AI, Voice of Customer, and automatic QA. Our outcome-based model prioritizes measurable results for more than 200 client programs serviced today. With a focus on automation, talent enablement, strategic partnerships, and strict data ethics, UnifyCX delivers scalable, personalized, and compliant solutions that create real business impact.<br>
<br>
At unifyCX, we leverage advanced AI technologies to elevate the customer experience (CX) and drive operational efficiency for our clients. Our commitment to innovation positions us as a trusted partner, enabling businesses across industries to meet the evolving demands of a global market with agility and precision. unifyCX is a certified minority-owned business and an EOE employer who welcomes diversity.<br>
<br>
<b>First Key Projects:</b><br>
Develop the infrastructure needed for ML workloads, including cloud services, containerization, and orchestration tools.<br>
<br>
<b>Key Responsibilities:</b><br>
<ul><li>Model Deployment &amp; Monitoring: Design, implement, and manage the deployment pipelines for machine learning models. Monitor model performance and ensure the stability and scalability of production systems.</li><li>Infrastructure Management: Develop and maintain the infrastructure needed for ML workloads, including cloud services, containerization, and orchestration tools.</li><li>Automation: Automate the ML lifecycle processes, including data ingestion, model training, testing, and deployment.</li><li>Collaboration: Work closely with data scientists and engineers to understand model requirements and ensure seamless integration into production systems.</li><li>Version Control: Implement and manage version control systems for ML models, datasets, and code.</li><li>Performance Tuning: Optimize ML models and systems for performance, cost, and efficiency. Troubleshoot and resolve issues that arise in production environments.</li><li>Security &amp; Compliance: Ensure that all ML systems and processes comply with security policies and regulatory requirements.</li><li>Documentation &amp; Reporting: Document processes, best practices, and workflows. Provide regular reports on system performance, issues, and improvements.</li></ul>
<br>
<b>Required Skillsets:</b><br>
<ul><li>Bachelor&rsquo;s degree in Computer Science, Data Engineering, or related field.</li><li>3+ years of experience in ML Ops, DevOps, or Data Engineering.</li><li>Strong proficiency with Python and Linux-based systems.</li><li>Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).</li><li>Proficiency with containerization (Docker) and orchestration (Kubernetes).</li><li>Experience with cloud platforms (AWS Sagemaker, GCP Vertex AI, or Azure ML).</li><li>Familiarity with CI/CD pipelines and infrastructure-as-code tools (Terraform, CloudFormation).</li></ul>
<br>
<b>Preferred Skillsets:</b><br>
<ul><li>Experience with feature stores (Feast, Tecton, etc.).</li><li>Knowledge of data pipelines and orchestration tools (Airflow, Prefect, Dagster).</li><li>Background in MLOps frameworks (MLflow, Kubeflow, BentoML, DVC).</li><li>Experience implementing model monitoring and drift detection.</li><li>Strong understanding of software engineering best practices and agile workflows.</li></ul></div>

ML Ops Engineer

W2S Solutions

<p>Role: <b>Junior ML Ops Engineer</b></p><p>Work Mode: <b>Onsite/Full time</b></p><p>Location: <b>Chennai, Sholinganallur</b></p><p>Year of Experience: <b>3 - 5 years </b></p><p>Notice Period: <b>Immediate or 15 days</b></p><p><b>Good To Have Skills: </b>Good communication</p><p><b>Must Have Skills: </b>Azure, MLOPS, Open AI/Generative AI, Continuous integration (CI) and continuous delivery (CD), Python</p><p><b>External Description:</b></p><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><p>Interested candidates can reach us at <b>@7338773388 or careers@w2ssolutions.com, &amp; hr@way2smile.com</b></p><p>Job Types: Full-time, Permanent</p><p>Pay: &#8377;500,000.00 - &#8377;800,000.00 per year</p><p>Work Location: In person</p>

Junior ML Ops Engineer

FDM Group

<div><div><div><div><div><h2 class="jobSectionHeader"><b>About The Role</b></h2></div><b>
</b></div></div><div><div><div><div><p>This position requires the successful candidate to work on a W2 directly with FDM. We cannot accept C2C, 1099 or employment sponsorship (e.g. H1-B) for this position.</p>
<p>
FDM is a global business and technology consultancy delivering client and industry driven solutions through our 5 core specialist Practices; Software Engineering, Data &amp; Analytics, IT Operations, Change &amp; Transformation, and Risk, Regulation &amp; Compliance.</p>
<p>
FDM is seeking a <b>ML Ops Engineer </b>located in <b>Cary, NC </b>to support a project in the <b>Financial Services </b>sector. Involvement in this project is anticipated to last initially <b>12 month </b>but may be extended.</p>
<p>
This role will be <b>hybrid</b> with requirements to be in office <b>3</b> days per week.</p>
<div>
<p>We are seeking a skilled MLOps Engineer with deep expertise in Google Cloud Platform (GCP) to help us build a world-class machine learning and AI capabilities within the bank. You will be instrumental in designing, implementing, and maintaining scalable infrastructure and automated pipelines that support the full machine learning lifecycle&mdash;from experimentation to deployment and monitoring.</p>
<p></p>
<p>This role involves close collaboration with data scientists, data engineers, product managers, and platform teams to operationalize models, streamline workflows, and uphold the highest standards of security, privacy, and compliance. You&rsquo;ll help define and evolve our ML Ops practices, ensuring our AI solutions are reliable, reproducible, and impactful.</p><br>
<div></div>
<p>
Key Responsibilities</p>
<ul>
<li>Build and maintain CI/CD pipelines for ML workflows using GCP-native tools such as Cloud Build, Artifact Registry, and Cloud Deploy.</li>
<li>Containerize and orchestrate ML workloads using Docker, Kubernetes, and GKE (Google Kubernetes Engine).</li>
<li>Collaborate with cross-functional teams to transition models from development to production, integrating them into customer-facing applications.</li>
<li>Implement robust model monitoring, logging, and alerting using tools like Vertex AI Model Monitoring, Cloud Logging, and Cloud Monitoring.</li>
<li>Define and enforce best practices for model versioning, testing, and reproducibility using tools like MLflow and Vertex AI Pipelines.</li>
<li>Ensure infrastructure adheres to security and compliance standards, working closely with Cybersecurity and Data Governance teams.</li>
<li>Continuously evaluate and integrate emerging GCP technologies to enhance platform capabilities and delivery speed.</li>
</ul></div></div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>About You</b></h2></div><b>
</b></div></div><div><div><div><div><p><b>Required Skills &amp; Experience</b></p>
<ul>
<li>Bachelor&rsquo;s degree in Computer Science, Software Engineering, or related field.</li>
<li>5+ years of experience in MLOps or DevOps roles, with a strong focus on cloud-native ML infrastructure.</li>
<li>Proven experience deploying ML models in production (batch and real-time), ideally in regulated or privacy-sensitive environments.</li>
<li>Proficiency in Python, with solid software engineering fundamentals and experience using Terraform or Deployment Manager for infrastructure-as-code.</li>
<li>Hands-on experience with:
<ul><li>GCP ML tools: Vertex AI, AI Platform, BigQuery ML</li>
<li>CI/CD: Cloud Build, GitHub Actions, Jenkins</li>
Containerization &amp; Orchestration: Docker, Kubernetes, GKE<br>
<li>
</li></ul></li></ul><p></p><p><b>Preferred Qualifications</b></p>
<ul>
<li>Experience deploying and managing generative AI models (LLMs) in production, including prompt engineering, evaluation pipelines, and safety guardrails.</li>
<li>Familiarity with observability tools such as MLflow, LangFuse, or Braintrust.</li>
<li>Exposure to data governance and privacy frameworks in cloud environments.</li>
</ul></div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>About Us</b></h2></div><b>
</b></div></div><div><div><div><div><p><b>About FDM</b></p>
<p>
FDM is an award-winning global business and technology consultancy powering the people behind tech and innovation for over 30 years. We collaborate with world-leading companies to identify the expertise they need, exactly when they need it. We have helped successfully launch nearly 25,000 careers globally to date and are a trusted partner to over 300 companies worldwide.</p>
<p>
FDM has 2500+ employees worldwide, with over 80 nationalities working together as a team. From our origins in Brighton, UK, FDM now has 19 centers located across North America, Europe and Asia-Pacific and is now on the FTSE4Good Index.</p>
<p></p>
<p><b>Dedicated to Diversity, Equity and Inclusion</b></p>
<p>
FDM Group&rsquo;s mission is to make tech and business careers accessible for everyone. Our diverse team of 80+ nationalities thrive on differences, fuels innovation through varied experiences, and celebrates shared successes. As an Equal Opportunity Employer that is listed on the FTSE4Good Index, FDM ensures every qualified applicant, regardless of race, color, religion, sex, sexual orientation, national origin, age, disability or any other status protected by federal or provincial law, gets the chance they deserve.</p><br>
<p></p>
<p>
FDM Group, Inc. is registered to operate and hire employees in select states within the US. We will consider employment applications exclusively from candidates who are either residing in one of the following states or willing to relocate to them: Arizona, California, Colorado, Delaware, Florida, Georgia, Illinois, Indiana, Massachusetts, Maryland, Maine, Minnesota, North Carolina, New Jersey, New York, Pennsylvania, Tennessee, Texas, Utah, and Virginia.</p></div></div></div></div></div><p></p><div><div><div><br>
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ML Ops Engineer (experienced) - Cary, NC

SKILLZREVO SOLUTIONS PVT LTD

<p><b>Location: Pune / Mumbai / Bangalore / Hyderabad / Gurugram / Chandigarh</b></p><p><b>Shift Timings : 3:30 PM to 12:30 AM</b></p><p><b>Budget: Up to &#8377;18 LPA (negotiable for exceptional candidates)</b></p><p><b>Mandatory Requirements:</b></p><p>Strong Python and API development skills</p><p>Hands-on with SQL/NoSQL databases</p><p>Practical exposure to MLOps tools: Docker, Kubernetes, MLflow</p><p>Experience deploying and managing ML services on cloud platforms</p><p>Bonus: Model monitoring (Prometheus, Grafana), orchestration (Airflow, Kubeflow), A/B testing</p><p>Job Types: Full-time, Permanent</p><p>Pay: &#8377;125,000.00 - &#8377;141,000.00 per month</p><p>Benefits:</p><ul><li>Health insurance</li><li>Provident Fund</li></ul><p>Work Location: In person</p>

Senior ML Ops Engineer

Sandisk

<div>
 <strong>
  Company Description
  <br/>
  <br/>
 </strong>
 Sandisk understands how people and businesses consume data and we relentlessly innovate to deliver solutions that enable today&rsquo;s needs and tomorrow&rsquo;s next big ideas. With a rich history of groundbreaking innovations in Flash and advanced memory technologies, our solutions have become the beating heart of the digital world we&rsquo;re living in and that we have the power to shape.
 <br/>
 <br/>
 Sandisk meets people and businesses at the intersection of their aspirations and the moment, enabling them to keep moving and pushing possibility forward. We do this through the balance of our powerhouse manufacturing capabilities and our industry-leading portfolio of products that are recognized globally for innovation, performance and quality.
 <br/>
 <br/>
 Sandisk has two facilities recognized by the World Economic Forum as part of the Global Lighthouse Network for advanced 4IR innovations. These facilities were also recognized as Sustainability Lighthouses for breakthroughs in efficient operations. With our global reach, we ensure the global supply chain has access to the Flash memory it needs to keep our world moving forward.
 <br/>
 <br/>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 We are seeking a
 <strong>
  ML Ops Engineer
 </strong>
 with expertise in
 <strong>
  Python, ML Frameworks, Model lifecycle, Cloud platforms &amp;Tableau/PBI
 </strong>
 to join our team.
 <br/>
 <br/>
 <strong>
  Duties And Responsibilities
  <br/>
  <br/>
 </strong>
 Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models.
 <br/>
 <br/>
 Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes.
 <br/>
 <br/>
 Automate the training, testing and deployment processes for machine learning models.
 <br/>
 <br/>
 Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability.
 <br/>
 <br/>
 Implement best practices for version control, model reproducibility and governance.
 <br/>
 <br/>
 Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness.
 <br/>
 <br/>
 Troubleshoot and resolve issues related to model deployment and performance.
 <br/>
 <br/>
 Ensure compliance with security and data privacy standards in all MLOps activities.
 <br/>
 <br/>
 Keep up-to-date with the latest MLOps tools, technologies and trends.
 <br/>
 <br/>
 Provide support and guidance to other team members on MLOps practices.
 <br/>
 <br/>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <strong>
  Required skills and experience
  <br/>
  <br/>
 </strong>
 3-5 years of experience in MLOps, DevOps or a related field.
 <br/>
 <br/>
 Bachelor&rsquo;s degree in Computer Science, Data Science or a related field.
 <br/>
 <br/>
 Strong understanding of machine learning principles and model lifecycle management.
 <br/>
 <br/>
 Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
 <br/>
 <br/>
 Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective machine learning services.
 <br/>
 <br/>
 Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
 <br/>
 <br/>
 Knowledge of CI/CD pipelines, automation tools and version control systems like Git.
 <br/>
 <br/>
 Ability to create dashboards and visualize the data quickly in tools like tableau, power bi, apache superset ,etc
 <br/>
 <br/>
 Strong problem-solving skills and ability to troubleshoot complex issues.
 <br/>
 <br/>
 Experience with monitoring tools and practices for model performance in production.
 <br/>
 <br/>
 Ability to work collaboratively in cross-functional teams.
 <br/>
 <br/>
 <strong>
  Nice To Have/preferred Skills And Experience
  <br/>
  <br/>
 </strong>
 Experience with infrastructure-as-code (IaC) tools such as Terraform or CloudFormation.
 <br/>
 <br/>
 Knowledge of big data technologies like Apache Spark or Hadoop.
 <br/>
 <br/>
 Familiarity with data engineering practices and tools.
 <br/>
 <br/>
 Experience with A/B testing and model validation in production environments.
 <br/>
 <br/>
 Relevant MLOps certifications (e.g., AWS Certified Machine Learning &ndash; Specialty, DataRobot MLOps Certification) are a plus.
 <br/>
 <br/>
 <strong>
  Additional Information
  <br/>
  <br/>
 </strong>
 Sandisk thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.
 <br/>
 <br/>
 Sandisk is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at jobs.accommodations@sandisk.com to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.
</div>


Senior Engineer, Industrial Engineering (ML Ops Engineer with 3-5 Yrs Exp)

Motive

<div><div><p><b>Who we are:</b></p>
<p>
Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks.</p>
<p>
Motive serves nearly 100,000 customers &ndash; from Fortune 500 enterprises to small businesses &ndash; across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector.</p>
<p>
Visit gomotive.com to learn more.</p></div><div><h3 class="jobSectionHeader"><b>
About the Role:</b></h3>
<p>
As a Software Engineer on the <b>ML Platform team</b>, you will lead the effort to build systems that enable AI R&amp;D teams to deliver secure, highly scalable, distributed services. You will leverage technology such as Kubeflow, Kubernetes, Helm, Terraform, Python to build inference systems, infrastructure, and training pipelines as well as the distributed systems themselves. You will also provide guidance and mentorship to junior engineers.</p>
<h3 class="jobSectionHeader"><b>
What You'll Do:</b></h3>
<ul><li>Help define the direction for the team.</li>
<li>Define and prioritize ML Platform initiatives.</li>
<li>Enable teams to build features at scale by providing a foundation of reusable software components and infrastructure.</li>
<li>Become one of the subject matter experts on the team. Create deployment pipelines; take code from git to production.</li>
<li>Build infrastructure that enables fast, robust automated testing and validation.</li>
<li>Improve the performance and reliability of existing systems.</li>
<li>Coach junior engineers.</li>
</ul><h3 class="jobSectionHeader"><b>What We're Looking For:</b></h3>
<ul><li>Building ML Ops infrastructure such as training pipelines.</li>
<li>Building services to deliver inference in a scalable manner.</li>
<li>Establishing monitoring best practices and implementing systems to enforce them.</li>
<li>Practicing and advocating for best engineering practices throughout the ML org.</li>
<li>B.S. or M.S. in Computer Science or a related field</li>
<li>3+ years software development experience</li>
<li>Experience improving the ML infrastructure with multiple stakeholders in a large organization.</li>
<li>Experience in Python or similar language.</li>
<li>Working knowledge of AWS services and technologies.</li>
<li>Experience with Kubeflow pipeline development and management.</li>
<li>Nice to have exposure with infrastructure as code and configuration management such as Terraform, CloudFormation.</li></ul></div><p></p><div><p><i><br>
Creating a diverse and inclusive workplace is one of Motive's core values. We are an equal opportunity employer and welcome people of different backgrounds, experiences, abilities and perspectives.</i></p><p></p><p><i><br>
</i></p><p><i>
The applicant must be authorized to receive and access those commodities and technologies controlled under U.S. Export Administration Regulations. </i><i>It is Motive's policy to require that employees be authorized to receive access to Motive products and technology.</i></p>
<p>
#LI-Remote</p></div></div>

Software Engineer - ML Platform

Leapcodes Private Limited

<p>We are seeking an experienced <b>AI/ML Engineer</b> to design, develop, and deploy scalable machine learning and AI solutions across our digital ecosystem. The ideal candidate will collaborate with data scientists, engineers, and domain experts to transform large datasets into actionable insights and AI-driven applications that enhance research and operational efficiency.</p><p><b>Key Responsibilities</b></p><ul><li>Design, develop, train, and deploy <b>machine learning (ML)</b> and <b>deep learning (DL)</b> models for life sciences and manufacturing use cases.</li><li>Collaborate with cross-functional teams to identify opportunities for AI/ML-driven automation and optimization.</li><li>Implement <b>end-to-end ML pipelines</b> &ndash; from data ingestion and feature engineering to model training, validation, and deployment.</li><li>Work with <b>big data platforms</b> (Databricks, Snowflake, AWS Sagemaker, Azure ML, etc.) to manage and process large-scale datasets.</li><li>Develop <b>NLP, computer vision, or predictive analytics</b> models for applications in research, digital labs, and customer analytics.</li><li>Collaborate with software engineering teams to <b>productionize and integrate AI models</b> into enterprise applications.</li><li>Conduct performance tuning, model monitoring, and continuous retraining as needed.</li><li>Stay updated with emerging trends in AI/ML technologies and tools.</li></ul><p><b>Required Skills and Qualifications</b></p><ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in <b>Computer Science, Data Science, Statistics, or related field</b>.</li><li>Proficiency in <b>Python</b>, <b>SQL</b>, and ML frameworks such as <b>TensorFlow</b>, <b>PyTorch</b>, <b>Scikit-learn</b>, <b>XGBoost</b>, or <b>LightGBM</b>.</li><li>Strong understanding of <b>data structures, algorithms</b>, and <b>statistics</b>.</li><li>Experience with <b>cloud-based ML platforms</b> &ndash; AWS SageMaker, Azure ML, or GCP Vertex AI.</li><li>Hands-on experience in <b>MLOps</b> &ndash; model versioning, CI/CD, and monitoring using tools like MLflow, Kubeflow, or Airflow.</li><li>Exposure to <b>NLP, computer vision</b>, or <b>time-series forecasting</b> techniques.</li><li>Excellent problem-solving, communication, and collaboration skills.</li></ul><p><b>Preferred Qualifications</b></p><ul><li>Experience in <b>Life Sciences / Healthcare / Pharma / Biotech</b> domains.</li><li>Familiarity with <b>data engineering</b> tools like Databricks, Apache Spark, or Snowflake.</li><li>Knowledge of <b>GenAI</b> and <b>LLM fine-tuning</b> (e.g., OpenAI, Hugging Face, LangChain).</li><li>Experience deploying models as REST APIs or microservices using Flask/FastAPI.</li><li>Understanding of <b>data governance, model ethics, and regulatory compliance</b> in AI applications.</li><li>Work on impactful projects driving innovation in healthcare and life sciences.</li><li>Collaborate with global teams across R&amp;D, engineering, and data science.</li><li>Access to cutting-edge AI/ML platforms and technology ecosystem.</li><li>Inclusive, diverse, and innovation-driven culture.</li></ul><p>Job Type: Full-time</p><p>Pay: &#8377;600,000.00 - &#8377;1,200,000.00 per year</p><p>Work Location: In person</p>

AI/ML : Engineers & Architect

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