machine learning operations engineer

Finaira

<div><p>The MLOps Engineer II will independently design, implement, and manage the automation and streamlining of the machine learning lifecycle, ensuring reliable, efficient, and scalable deployment and monitoring of models. This role requires a solid understanding of DevOps practices, cloud technologies, and machine learning frameworks, with the ability to bridge the gap between data science and operations effectively.</p><p></p><p><b>
Focus</b>: Independent automation of ML pipelines, deployment strategies, and monitoring in production.</p><p><b>
The difference you will make:</b></p><ul>
<li>
Independently design and implement CI/CD pipelines for machine learning models.</li>
<li>Automate the process of model training, validation, testing, and deployment using relevant tools.</li>
<li>Develop and maintain automated testing frameworks for machine learning models.</li>
<li>Develop and manage various model deployment strategies (e.g., A/B testing, canary deployments).</li>
<li>Build and maintain scalable and reliable infrastructure for model serving (e.g., using Kubernetes, serverless functions).</li>
<li>Implement and manage model versioning and rollback mechanisms.</li>
<li>Optimize model serving for latency, throughput, and resource utilization.</li>
<li>Implement and manage comprehensive monitoring and logging systems to track model performance and identify issues (e.g., model drift, data drift).</li>
<li>Set up and manage alerting systems to notify the team of performance degradation.</li>
<li>Contribute to the development and implementation of model governance policies and procedures.</li>
<li>Ensure compliance with security and privacy requirements.</li>
<li>Collaborate effectively with data scientists to understand model requirements and dependencies.</li>
<li>Work with software engineers to integrate machine learning models into applications and services.</li>
<li>Develop and maintain APIs and interfaces for model access.</li>
</ul><p><b>
Requirements</b></p><ul>
<li>
Education: Bachelor&rsquo;s degree in computer science, Engineering, or a related field.</li>
<li>Experience: 2+ years of experience in DevOps, software engineering, or a related role with a focus on machine learning deployment and operations. Proven experience with cloud platforms and containerization technologies. Experience in the financial services industry is a plus.</li>
<li>Technical Skills:</li></ul><ul>
<li>Strong proficiency in DevOps practices and tools (e.g., Jenkins, GitLab CI, Docker, Kubernetes).</li>
<li>Solid knowledge of cloud computing platforms (e.g., AWS, Azure, GCP) and their machine learning services.</li>
<li>Knowledge of MLflow or Kubeflow for model management, or similar.</li>
<li>Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).</li>
<li>Strong experience with scripting and automation (e.g., Python, Bash).</li>
<li>Solid understanding of software engineering principles and best practices.</li>
<li>Experience with infrastructure as code (IaC) tools (e.g., Terraform, CloudFormation).</li>
</ul><p></p><p><b>
Soft Skills:</b></p><ul>
<li>
Strong problem-solving and analytical skills with the ability to work independently.</li>
<li>Ability to work in a fast-paced and dynamic environment.</li>
<li>Automation mindset and a drive to improve efficiency.</li>
<li>Excellent collaboration and communication skills.</li>
<li>Customer-centric approach to solution development.</li>
<li>Strong team player.</li>
<li>Disciplined work ethic.</li>
<li>Good command of English language, both verbal and written.</li>
<li>Self-learner with a positive attitude.</li>
</ul><p></p><p>
Finaira is an Equal Opportunity Employer and is committed to providing a workplace free of discrimination and harassment. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by the laws or regulations in the locations where we operate.</p></div><p></p>

Mlops Engineer II

Liquid Technologies

<p>Liquid Technologies (LiqTeq) is an end-to-end Design and Development Agency. We offervarious services in DevOps, Data services and AI to multiple businesses and organizations and those that are in the startup phase. We're a team of creators, thinkers, explorers and judo trainees. We approach work and play with curiosity and experimentation, using what we learn to create meaningful digital products that connect with people.</p><p>We are looking to add a <b>ML Engineer </b>to join our <b>Karachi</b> office.</p><p><b>Key Responsibilities:</b></p><ul><li>Deploy, monitor, and manage machine learning models in production environments.</li><li>Develop and maintain scalable ML pipelines for training and inference.</li><li>Automate model retraining and deployment using CI/CD workflows.</li><li>Optimize cloud and on-prem infrastructure for ML workloads.</li><li>Implement monitoring, logging, and alerting for model performance and drift detection.</li><li>Ensure reproducibility, version control, and governance for ML models.</li><li>Collaborate with data scientists to optimize model deployment strategies.</li><li>Work with Kubernetes, Docker, and cloud platforms (AWS, GCP, Azure) for model hosting.</li><li>Manage feature stores, model registries, and data pipelines.</li></ul><p><b>Required Skills &amp; Qualifications:</b></p><ul><li>Bachelor's or Master&rsquo;s degree in Computer Science, AI, Data Science, or a related field.</li><li><b>Proficiency in Python</b> and ML frameworks (TensorFlow, PyTorch, Scikit-learn).</li><li>Experience with <b>ML pipeline orchestration</b> tools like Kubeflow, Airflow, or MLflow.</li><li>Strong knowledge of <b>DevOps &amp; CI/CD</b> practices for ML (Git, Jenkins, Docker, Kubernetes).</li><li>Familiarity with cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML).</li><li>Experience in model monitoring, logging, and automated retraining.</li><li>Understanding of data engineering, feature stores, and ETL pipelines.</li><li>Strong problem-solving and collaboration skills.</li><li>Previous experience in applying machine learning to service sector domains, such as retail, hospitality, transportation, or similar, is a plus.</li><li>Knowledge of cloud platforms (e.g AWS, Azure, GCP) and their machine learning services are advantageous.</li><li>Excellent communication skills to convey technical concepts to diverse audiences effectively.</li></ul><p>Job Type: Full-time</p><p>Application Question(s):</p><ul><li>Have you completed the following level of education: Bachelor's Degree?</li><li>What's your Current Salary?</li><li>What's your Expected Salary?</li><li>If selected, how soon can you join us?</li><li>Are you comfortable to commute to Zamzama?</li><li>Have you deployed machine learning models to a production environment using Docker and/or Kubernetes? </li><li>How many years of hands-on experience do you have working with machine learning pipelines (training, deployment, monitoring)?</li><li>Have you used any cloud ML services (e.g., AWS SageMaker, GCP Vertex AI, Azure ML) in a real project? </li></ul><p>Work Location: In person</p>

ML Engineer

Futops Technologies India Pvt. Ltd.

<p><b>Job Overview</b><br/>We are seeking a dynamic and detail-oriented ML Ops Engineer to drive the deployment, monitoring, and optimization of machine learning models within our cutting-edge environment. In this role, you will bridge the gap between data science and production systems, ensuring scalable, reliable, and efficient machine learning workflows. Your expertise will empower our teams to deliver innovative AI solutions that make a real impact. If you thrive in a fast-paced setting and are passionate about operational excellence in machine learning, this is your chance to contribute to transformative projects.</p><p><b>Responsibilities</b></p><ul><li>Design, develop, and maintain scalable infrastructure for deploying machine learning models in production environments</li><li>Automate model training, validation, deployment, and monitoring pipelines to ensure continuous integration and delivery</li><li>Collaborate with data scientists to optimize model performance and troubleshoot issues in real-time</li><li>Implement robust monitoring systems to track model accuracy, latency, resource utilization, and detect anomalies</li><li>Manage version control for models and datasets to facilitate reproducibility and compliance</li><li>Integrate quantum engineering principles where applicable to enhance computational efficiency and problem-solving capabilities</li><li>Ensure security best practices are followed throughout the ML lifecycle to protect sensitive data and intellectual property</li></ul><p><b>Requirements</b></p><ul><li>Proven experience in ML Ops or related roles with a strong understanding of deploying machine learning models at scale</li><li>Proficiency with cloud platforms such as AWS, Azure, or GCP for infrastructure management</li><li>Hands-on experience with containerization tools like Docker and orchestration frameworks such as Kubernetes</li><li>Familiarity with CI/CD pipelines tailored for machine learning workflows</li><li>Solid scripting skills in Python or similar languages for automation tasks</li><li>Knowledge of quantum engineering concepts is highly desirable to support advanced computational techniques</li><li>Excellent problem-solving skills with a proactive approach to troubleshooting complex systems</li></ul><p>Join us in shaping the future of intelligent technology! We are committed to fostering an inclusive environment where innovation thrives. This paid position offers an exciting opportunity to work at the forefront of AI development while advancing your career in a vibrant team dedicated to excellence.</p><p>Job Type: Full-time</p><p>Pay: ₹1,000,000.00 - ₹2,000,000.00 per year</p><p>Benefits:</p><ul><li>Health insurance</li></ul><p>Work Location: In person</p>

ML Ops Engineer

Capgemini

<div><div><div><p>Hyderabad, Bangalore</p><div>
MLOps Engineer</div><p>
</p></div></div><div></div><div><div><div><div><div><p>
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you&rsquo;d like, where you&rsquo;ll be supported and inspired by a collaborative community of colleagues around the world, and where you&rsquo;ll be able to reimagine what&rsquo;s possible. Join us and help the world&rsquo;s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
</p><div><div><div><div><b>Your Role</b></div></div><div><ul><li>
Design, implement, and maintain end-to-end ML pipelines for model training, evaluation, and deployment</li></ul><ul><li>
Collaborate with data scientists and software engineers to operationalize ML models, serving frameworks (TensorFlow Serving, TorchServe) and experience with MLOps tools</li></ul><ul><li>
Develop and maintain CI/CD pipelines for ML workflows</li></ul><ul><li>
Implement monitoring and logging solutions for ML models, experience with ML model serving frameworks (TensorFlow Serving, TorchServe)</li></ul><ul><li>
Optimize ML infrastructure for performance, scalability, and cost-efficiency</li></ul></div></div><div><div><div><b>
Your Profile</b></div></div><div><ul><li>
Strong programming skills in Python (5+ years), with experience in ML frameworks; understanding of ML-specific testing and validation techniques</li><li>
Expertise in containerization technologies (Docker) and orchestration platforms (Kubernetes), Knowledge of data versioning and model versioning techniques</li><li>
Proficiency in cloud platform (AWS) and their ML-specific services with atleast 2-3 years of experience.</li><li>
Strong understanding of DevOps practices and tools (GitLab, Artifactory, Gitflow etc.)</li><li>
Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack) and knowledge of distributed training techniques</li></ul></div></div><div><div><div><b>
What you&rsquo;ll love about working here</b></div></div><div><ul><li>
We recognise the significance of flexible work arrangements to provide support in hybrid mode, you will get an environment to maintain healthy work life balance</li><li>
Our focus will be your career growth &amp; professional development to support you in exploring the world of opportunities.</li><li>
Equip yourself with valuable certifications &amp; training programmes in the latest technologies such as MLOps, Machine Learning</li></ul><p>
</p></div></div></div><p></p><p>Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.</p></div></div><div><div><div>
<div><div>Ref. code</div><div>
326073-en_GB</div></div><div><div>
Posted on</div><div>
10 Sep 2025</div></div><div><div>
Experience level</div><div>
Experienced Professionals</div></div><div><div>
Contract type</div><div>
Permanent</div></div><div><div>
Location</div><div>
Hyderabad, Bangalore</div></div><div><div>
Business unit</div><div>
I and D Global Business Line</div></div><div><div>
Brand</div><div>
Capgemini</div></div></div></div></div></div></div></div></div><p></p>

MLOps Engineer

Persistent Systems

<div><div><div><p><b>Job Description
</b></p></div><div><div><div><p><b>
About Persistent</b></p><br>
<p></p>
<p>We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what&rsquo;s next. Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above. We work with many industry-leading organizations across the world, including 20 Fortune 50 companies and 4 of the 5 top banks in both the US and India, and numerous innovators across the healthcare ecosystem.<br>
</p><p>Our disruptor&rsquo;s mindset, commitment to client success, and agility to thrive in the dynamic environment have enabled us to sustain our growth momentum. Persistent has been recognized across top industry platforms for innovation, leadership, and inclusion. We have delivered 22 sequential quarters of growth with $406.2M in Q2 FY26 revenue, up 4.2% Q-o-Q and 17.6% Y-o-Y growth. Our 26,000+ global team members, located in 18 countries, have been instrumental in helping the market leaders transform their industries. We have been named the fastest-growing Indian IT services brand in the &ldquo;Brand Finance India 100&rdquo; 2025 report. We were also cited as a Leader in the ISG Provider Lens&trade; 2025 for Digital Engineering Services 2025 and the Everest Group Talent Readiness for Next-generation Application Services PEAK Matrix&reg; Assessment 2025</p><br>
<p></p>
<p><b>About Position:</b></p><br>
<p></p><p>We are seeking an experienced LLMOps and AIOps Engineer to design, deploy, and manage Large Language Model (LLM) workflows and AI-driven solutions.</p><br>
<p></p>
<ul><li><b>Role: LLMOps and AIOps Engineer</b></li>
<li><b>Location: Bangalore</b></li>
<li><b>Experience: 8 to 12 years</b></li>
<li><b>Job Type: Full Time Employment</b></li></ul><p><br>
</p><p><br>
<b>What You'll Do:</b></p><br>
<p></p>
<ul><li>This role involves integrating advanced AI capabilities into enterprise systems, enhancing automation, and ensuring reliable, scalable operations across cloud environments.</li>
<li>Deploy and manage Large Language Models using cloud-based or API-driven platforms. Build and maintain workflows for model invocation, prompt handling, and response processing.
</li><li>Develop retrieval-based features using vector databases for improved information access and automation. Monitor model performance, usage patterns, latency, and cost to ensure operational efficiency.
</li><li>Create lightweight scripts, APIs, or utilities to automate repetitive tasks and improve responsiveness. Implement observability components such as logging, quality checks, and performance metrics.
</li><li>Support CI/CD practices for automated deployments and updates of LLM-related services. Collaborate with engineering, data, and platform teams to integrate AI features into existing solutions.
</li><li>Document processes, best practices, and operational guidelines for consistency and maintainability.</li></ul><br>
<p>
</p><p><b>Expertise You'll Bring:</b></p><br>
<p></p><ul><li>Strong programming experience in Python for automation and API integrations. Hands-on experience with LLM platforms (OpenAI, Azure OpenAI, AWS Bedrock, or open-source models).</li>
<li>Knowledge of vector databases (Pinecone, Milvus, FAISS). Familiarity with retrieval-augmented workflows. Exposure to cloud services (Azure, AWS, GCP).
</li><li>Understanding of CI/CD concepts and version-controlled development practices. Ability to analyze model behaviour and manage operational issues proactively.
</li><li>Preferred Skills Experience with AI workflow frameworks (LangChain, LlamaIndex, Semantic Kernel).
</li><li>Basic knowledge of observability tools and metrics reporting. Exposure to containerization (Docker) or managed cloud runtimes. Understanding of modern APIs, microservices, or event-driven architectures.
</li><li>Interest in applied machine learning and responsible AI principles.</li></ul><br>
<p>
</p><p><b>Benefits:</b></p><br>
<p></p>
<ul><li>Competitive salary and benefits package</li>
<li>Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications</li>
<li>Opportunity to work with cutting-edge technologies</li>
<li>Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards</li>
<li>Annual health check-ups</li>
<li>Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents</li></ul><br>
<p>
</p><p><b>Values-Driven, People-Centric &amp; Inclusive Work Environment:</b></p><br>
<p></p>
<p>Persistent is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds.</p><br>
<p></p>
<ul><li>We support hybrid work and flexible hours to fit diverse lifestyles.</li>
<li>Our office is accessibility-friendly, with ergonomic setups and assistive technologies to support employees with physical disabilities.</li>
<li>If you are a person with disabilities and have specific requirements, please inform us during the application process or at any time during your employment</li></ul><br>
<p>
</p><p><b>Let&rsquo;s unleash your full potential at Persistent</b></p><br>
<p></p>
<p><b><i>&ldquo;Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.&rdquo;</i></b></p>
</div></div></div></div><div></div><div><div><div><p><b>
1</b></p></div><div><div>
Open Positions
</div></div></div></div><div><div><div><p><b>AI Ops,LLM,LLMOps</b></p></div><div><div>
Skills Required
</div></div></div></div><div><div><div><p><b>Bengaluru, Karnataka, India</b></p></div><div><div>
Location
</div></div></div></div><div><div><div><p><b>AI Ops,LLM,LLMOps</b></p></div><div><div>
Desirable Skills
</div></div></div></div><div><div><div><p><b>8 to 12 years</b></p></div><div><div>
Years Of Exp
</div></div></div></div><div><div><div><p><b>164489</b></p></div><div><div>
Job Code</div></div></div></div></div><p></p>

LLMOps and AIOps Engineer

Rapid Job Sountions

<p><b>Job Title: </b>Graduate Trainee Engineer (Production) &ndash; SPM Machines</p><p><b>Location:</b> Wagholi, Pune</p><p><b>Experience: </b>Fresher (0&ndash;3 year in automation industry)</p><p><b>Qualification:</b> B.E. / B.Tech in Mechanical Engineering</p><p><b>Job Summary : </b>We are looking for an enthusiastic Graduate Trainee Engineer to join our production team specializing in Special Purpose Machines (SPM). The role involves learning production processes, assisting in machine operations, understanding production planning, and supporting quality and safety practices.</p><p><b>Key Responsibilities :</b></p><ul><li>Assist in operating and maintaining Special Purpose Machines (SPM) under supervision.</li><li>Learn and support production scheduling to meet daily and weekly targets.</li><li>Observe and participate in troubleshooting activities for machine issues.</li><li>Contribute to process improvement initiatives to enhance productivity.</li><li>Assist in preventive maintenance to minimize downtime.</li><li>Follow quality control guidelines and safety procedures diligently.</li></ul><p><b>Skills Required: </b></p><ul><li>Basic knowledge of mechanical engineering principles.</li><li>Willingness to learn SPM machine operations and troubleshooting.</li><li>Ability to read and understand basic technical drawings.</li><li>Familiarity with CAD software (AutoCAD / SolidWorks) is a plus.</li><li>Strong analytical skills, eagerness to learn, and good teamwork.</li></ul><p>Job Types: Full-time, Permanent, Fresher</p><p>Pay: ₹15,000.00 - ₹25,000.00 per month</p><p>Benefits:</p><ul><li>Health insurance</li><li>Provident Fund</li></ul><p>Experience:</p><ul><li>Production engineer: 1 year (Required)</li><li>Fresher: 1 year (Required)</li></ul><p>Location:</p><ul><li>Wagholi, Pune, Maharashtra (Required)</li></ul><p>Work Location: In person</p>

Junior Production Engineer

VAM SYSTEMS

<div><b>Job Description</b><p><b><br>
VAM Systems </b>is currently looking for<b> AI/ML Specialists (Data Scientists/ ML Engineer) </b>(On-Site) for our<b> Bahrain </b>operations with the following skillsets and terms &amp; conditions:</p><p><b>
Years of Experience: 7 &ndash; 10 years</b></p><p><b>
Qualification</b></p><p>
Bachelor&rsquo;s Degree in Computer Science / Engineering<br>
Preferably BE Computer Science &amp; Engineering</p><p><b>
Professional Training Required: </b>Machine Learning, Deep Learning, MLOps, AI in Financial Services.<br>
<b>Professional Qualification Required: </b>Google Professional ML Engineer, Microsoft AI Engineer Associate Professional Licenses Required Not applicable.<br>
<b>Professional Certifications Required: </b>TensorFlow Developer Certificate, AWS Certified Machine Learning.</p><p><b>
Must-Have:</b></p><ul><li>Proven hands-on delivery experience in banking, financial institutions, or insurance within Gen AI solutions such as chatbots, document analysis, etc., leveraging RAG and robust architecture with proper governance and security measures</li><li>Several years of ML experience with implemented use cases.</li><li>Hands-on work experience most of which in banking, financial institutions, or insurance industries.</li></ul><p><b>
Experience required:</b></p><p>
Ability to build and deploy ML models using Python and relevant libraries. Understanding of supervised and unsupervised learning algorithms.<br>
Experience with model evaluation and performance metrics.</p><p>
Familiarity with AI use cases in banking (e.g., fraud detection, personalization) Knowledge of data preprocessing and feature engineering.<br>
Ability to work with cloud-based ML platforms (e.g., Azure ML, AWS SageMaker). Understanding of MLOps and model lifecycle management.<br>
Ability to communicate insights and build explainable AI models.<br>
<b>Joining time frame: (15 - 30 days)</b></p></div>

AI/ML Specialists (Data Scientists/ ML Engineer)

Search 10000+ Machine learning operations engineer jobs near you this January. New roles added regularly across leading industries. Apply today.