mlops engineer

Shag Infotech Pvt. Ltd.

Job Summary: Shag Infotech is seeking an MLOps Engineer to manage, deploy, and optimize machine learning models in production. The role focuses on ensuring scalable, reliable, and efficient AI/ML systems while collaborating with data scientists and development teams.Key Responsibilities:<ul><li>Deploy, monitor, and maintain machine learning models in production environments.</li><li>Automate ML workflows, pipelines, and continuous integration/continuous delivery (CI/CD) processes.</li><li>Collaborate with data scientists and engineers to ensure seamless integration of AI models.</li><li>Optimize system performance, reliability, and scalability for ML applications.</li><li>Implement monitoring, logging, and alerting solutions for ML models.</li><li>Evaluate and adopt emerging MLOps tools and best practices.</li></ul>Requirements:<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, AI, or related field.</li><li>2+ years of experience in MLOps, DevOps, or ML model deployment.</li><li>Strong knowledge of Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn).</li><li>Experience with cloud platforms (AWS, Azure, Google Cloud) and containerization (Docker, Kubernetes).</li><li>Familiarity with CI/CD pipelines, monitoring tools, and model versioning.</li><li>Strong problem-solving, collaboration, and communication skills.</li></ul>What We Offer:<ul><li>Work on innovative AI-driven projects in IT and marketing.</li><li>Collaborative and growth-focused work environment.</li><li>Competitive salary and performance-based incentives.</li></ul>Job Types: Full-time, PermanentPay: &#8377;259,910.20 - &#8377;1,076,777.98 per yearBenefits:<ul><li>Flexible schedule</li><li>Internet reimbursement</li></ul>Work Location: In person

MLOps Engineer

NewMind AI

<div>I - Who We Are?
New Mind AI is an innovative and pioneering company specializing in leveraging big data through a comprehensive and holistic approach. From data digitization and classification to deriving meaningful insights and extracting actionable outputs, we employ advanced taxonomies and ontologies to organize data in a structured and insightful manner, creating a semantic layer to better understand corporate data. Our mission extends beyond mere data structuring; we empower companies to transform their data into actionable insights, facilitating dynamic corporate governance.
With over 300 task-oriented and domain-specific AI models, built using an orchestration of experts framework, we provide robust solutions for dynamic corporate governance. By implementing dynamic knowledge network structures, we develop advanced AI models that ensure effective management of corporate data in the business world. Our expertise spans AI-driven business solutions, including AI legal tech products, excelling in natural language processing, deep learning, machine learning, data analysis, and data visualization.
Headquartered in YT&Uuml; Teknopark, Maslak, Istanbul, and operating four specialized laboratories&mdash;Data Visualization Lab in India, Data Taxonomy Lab in Bomonti, and Big Data and Legal Tech Labs in Maslak&mdash;we are leaders in big data analysis in T&uuml;rkiye and beyond. Our flagship dynamic knowledge management platforms, Mecellem, Malumat, and Mahfuz, empower professionals across various industries by streamlining complex tasks, optimizing decision-making, and managing business risks with precision.
Through our cutting-edge AI tools, including Generative AI, LLMs, text-to-speech and speech-to-text, image recognition, voice recognition, function call, graphRAG, OCR, blockchain and RAG, we set new standards in business technology. We deliver smarter, more dynamic solutions for the business world, both in T&uuml;rkiye and internationally. 
II - Who We Are Looking For?
We are seeking a skilled and experienced MLOps Engineer to join our team. The ideal candidate will have a strong understanding of MLOps/DataOps/AIOps/DevOps/LLMOps methodologies and principles, with expertise in building and maintaining robust MLOps infrastructure. This role requires proficiency in Python and Bash programming languages, experience with containerization technologies like Docker and Kubernetes, and familiarity with various MLOps frameworks and tools. The ideal candidate will be passionate about the engineering behind machine learning, with a strong understanding of data pipelines, model training, deployment, and monitoring. 
III - What Will Be Your Responsibilities?
(i) Design and implement scalable MLOps infrastructure, including orchestrated data pipelines, continuous model training and automated deployment systems. (ii) Develop and maintain monitoring and configuration management tools to ensure the reliability and performance of our on-premises MLOps infrastructure. (iii) Collaborate with data scientists and software engineers to build scalable and efficient data pipelines and model training and deployment systems. (iv) Install and configure hardware, operating systems, and related software for tuning computing resources. (v) Prepare development and production platforms for Machine Learning Operations with containerization technologies. (vi) Communicate with a team of data scientists, machine learning engineers, and architects to document processes and ensure smooth collaboration. (vii) Troubleshoot and debug issues related to MLOps infrastructure and deployment processes. (viii) Take offline models built by Machine Learning Engineers and turn them into real machine learning production systems. (ix) Stay up-to-date with the latest trends and technologies in MLOps, LLMOps, machine learning, and artificial intelligence. 
IV - What Is Required from You?
(i) Qualifications: Bachelor's degree in Computer Engineering, Data Science, or a related field. Master's or PhD degree is a plus. (ii) Experience: 2+ years of hands-on experience in designing and implementing MLOps solutions, including experience with containerization technologies, CI/CD pipelines, and data pipeline orchestration platforms. (iii) Expertise: Strong understanding of MLOps/DataOps/AIOps/DevOps/LLMOps methodologies and principles. Proficiency in Python and Bash programming languages. Experience with Machine Learning frameworks - like scikit-learn, LGBM, TensorFlow, PyTorch etc. Experience with MLOps Frameworks like MLFlow, Kedro, W&amp;B, DVC etc. Experience with at least one Machine Learning/Data Pipeline orchestration platform such as Apache Airflow, MageAI, Kubeflow etc. Experience with big data processing frameworks such as Apache Spark and streaming platforms like Apache Kafka. Familiarity with data formats including Parquet files and data lakehouse technologies such as Apache Hudi. Strong knowledge of containerization with Docker and container orchestration technologies, such as Docker Swarm, Kubernetes, Slurm etc. Experience with Kubernetes backup and disaster recovery tools such as Velero. (iv) Knowledge: Strong knowledge of infrastructure monitoring tools such as Prometheus, Grafana, Evidently, Zabbix etc. Experience with Configuration Management tools such as Ansible, Chef, Puppet, Terraform etc. Hands-on experience in Linux (Debian Based) and administration. Experience working with cloud computing and database systems such as Elasticsearch, MongoDB, MySQL, Postgres, Couchbase etc. Knowledge of distributed storage systems such as Ceph and object storage solutions like Minio. Understanding of GPU virtualization technologies including MIG (Multi-Instance GPU) and MPS (Multi-Process Service). Expertise on VCS systems such as Gitlab, Github etc. (v) Skills: Self-motivated, organized, proactive, and flexible. Passion for the engineering behind machine learning and scaling it. Experience with DevOps and CI/CD practices. Strong Understanding cluster based microservice infrastructures in High Availability and fault-tolerant systems. Hands-on experience on Data Migration and Version Bump Operations. Understanding Network fundamentals and configuration management, troubleshooting. Hands-on experience on Zero downtime deployment operations. Experience with reverse proxying and load balancing technologies such as Nginx, HAProxy, Traefik, Envoy etc. Ability to design and implement build MLOps pipelines on premise/cloud. Ability to understand tools used by Machine Learning Engineers and experience with software development and test automation. Experience with Agile methodologies and Scrum frameworks. Hands-on experience on Virtual Machines, including hypervisors (Hyper-V, ESXi etc.). (vi) Language: Fluent in English, both written and spoken, is required for effective communication with international teams and clients. (vii) Competencies: Strong analytical and problem-solving skills. Excellent communication and collaboration skills. Ability to work independently and as part of a team. Passion for AI and its potential to transform businesses. 
V - Why Work at New Mind AI?
New Mind AI offers a unique opportunity for ambitious young professionals seeking to make a real impact in the rapidly growing field of AI. As a company at the forefront of AI innovation, we are driven by a strong mission to empower businesses with actionable insights derived from data. This translates to a dynamic and stimulating work environment where you will be challenged to think critically, develop your skills, and contribute to groundbreaking projects. Here are some key reasons why New Mind is an ideal place for young talent: (i) be a part of something bigger: Our work goes beyond simply developing AI models. We are shaping the future of business and helping organizations navigate the complex world of data-driven decision-making; (ii) work with leading experts: You will be surrounded by a team of passionate and knowledgeable individuals who are experts in their fields. This collaborative environment fosters continuous learning and growth; (iii) gain valuable experience: You will have the opportunity to work on diverse projects, utilizing cutting-edge AI tools and technologies, including Generative AI, LLMs, and more; (iv) make a real difference: Your contributions will directly impact our company's growth and success, contributing to the advancement of AI technology and its positive impact on the world; (v) global reach: As a company with a global presence, you will be exposed to a diverse range of perspectives and opportunities to work with clients and partners from around the world; (vi) invest in your future: New Mind is committed to supporting its employees' professional development and offers opportunities for growth within the company.</div>

blue chik software solutions

Job Title: - ML / MLOPs Engineer Location: - Noida (Sector- 132) Experience: 1+ year Brief Job Description: The ML/MLOps Engineer is responsible for developing, deploying, and maintaining machine learning models and ensuring their seamless integration into production systems. This role involves automating ML pipelines, optimisingg model performance, managing data workflows, and collaborating with data scientists, software engineers, and DevOpsteams to operationalisee AI/ML solutions efficiently. Required Qualifications:<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, Data Science, or a related field.</li><li>Minimum 1 year of experience in machine learning operations (MLOps), cloud engineering, or similar roles</li></ul>. &bull; Proficiency in Python, with hands-on experience using libraries such as TensorFlow, PyTorch, scikit-learn, Pandas, and NumPy.<ul><li>Strong experience with Azure Machine Learning services, including Azure ML Studio, Azure Databricks, and Azure Kubernetes Service (AKS).</li><li>Knowledge and experience in building end-to-end ML pipelines, deploying models, and automating the machine learning lifecycle.</li><li>Expertise in Docker, Kubernetes, and container orchestration for deploying machine learning models at scale.</li><li>Experience in data engineering practices and familiarity with cloud storage solutions like Azure Blob Storage and Azure Data Lake.</li><li>Strong understanding of NLP, CV, or GenAI programming, along with the ability to apply these techniques to real-world business problems.</li><li>Experience with Git, Azure DevOps, or similar tools to manage version control and CI/CD pipelines. &bull; Solid experience in machine learning algorithms, model training, evaluation, and hyperparameter tuning</li></ul>Share your CV to : hr.bluechik@gmail.comJob Types: Full-time, PermanentPay: &#8377;225,907.18 - &#8377;1,439,378.72 per yearBenefits:<ul><li>Provident Fund</li></ul>Work Location: In person

ML / MLOPs Engineer

Moody's

<div>At Moody's, we unite the brightest minds to turn today&rsquo;s risks into tomorrow&rsquo;s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are&mdash;with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody&rsquo;s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we&rsquo;re advancing AI to move from insight to action&mdash;enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.
If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.<div>
Skills and competencies 
<ul><li>Strong AWS ML deployment skills (SageMaker, Lambda, Glue, ECS/EKS, S3, CloudWatch) with AWS ML Specialty certification; experience in Azure, Terraform/CloudFormation, CI/CD pipelines, containerization, and orchestration.</li><li>Proficient in Python, ML frameworks, distributed training, optimization for large models, and GenAI deployment patterns including prompt engineering.</li><li>Solid understanding of ML/GenAI concepts, model monitoring, drift detection, and infrastructure automation.</li><li>Demonstrates strong work ethic, teamwork, clear communication, and excellent problem-solving skills</li><li>3&ndash;4+ years of hands-on experience in MLOps or related roles.</li></ul></div><div>
Education 
<ul><li>Bachelor&rsquo;s or master&rsquo;s degree in computer science, engineering, or a related field.</li></ul></div><div>
Roles and responsibilities 
<ul><li>Design and implement robust, scalable ML/GenAI deployment pipelines on AWS using services like Lambda, Glue, ECS/EKS, and Step Functions , along with open-source tools.</li><li>Automate model training, testing, and deployment workflows using CI/CD best practices.</li><li>Optimize inference performance and cost efficiency for large-scale ML and GenAI applications.</li><li>Collaborate with data scientists to productionize models and integrate them into business applications.</li><li>Design tools and processes to deploy multiple ML and GenAI solutions smoothly.</li><li>Implement monitoring, logging, and alerting for deployed models to ensure reliability and compliance.</li><li>Manage model versioning, governance, and lifecycle using tools like AWS-native solutions or open-source tools .</li><li>Ensure security and compliance of ML workloads, including IAM roles and data encryption.</li><li>Troubleshoot and resolve issues in ML pipelines and infrastructure.</li></ul></div>
About the team 
Moody&rsquo;s Ratings&rsquo; AI Analytics group develops advanced machine learning and generative AI solutions for high-profile data science initiatives. To strengthen our team, we seek an experienced Senior MLOps Engineer to design, deploy, and maintain production-grade machine learning (ML) and GenAI systems on AWS. The successful candidate will work closely with data scientists, data engineers, and cloud system engineers to operationalize models, ensuring scalability, reliability, and security across our AI ecosystem.
Moody&rsquo;s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law. 
 
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody&rsquo;s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.</div>

Senior MLOps Engineer

EPAM Systems

<div>We are seeking an experienced Senior MLOps Engineer to join our team and help operationalize and manage machine learning models. You will play a critical role in optimizing deployment processes, scaling infrastructure, and ensuring the reliability of machine learning solutions in production environments.
Responsibilities<ul><li>
Develop and maintain automation tools for continuous integration and deployment (CI/CD) of machine learning models</li><li>
Ensure robust monitoring, logging, and alerting systems for models in production to quickly identify and address any issues</li><li>
Collaborate closely with data scientists and data engineers to enhance model architectures and performance</li><li>
Manage the infrastructure and resources required for deploying models in production, including servers, data storage, and computational resources</li><li>
Implement version control and change management processes for machine learning models</li><li>
Proactively identify, diagnose, and resolve performance bottlenecks and anomalies in deployed models</li><li>
Enforce data security best practices and ensure compliance with regulatory requirements</li><li>
Stay updated on the latest advancements in machine learning technologies, tools, and industry standards</li></ul>
Requirements<ul><li>
A degree in Computer Science, Engineering, Statistics, or a related field</li><li>
3+ years of experience with MLOps workflows and practices</li><li>
Experience with tools such as Docker, Kubernetes, Jenkins, or similar for managing containerized applications and automating workflows</li><li>
Proficiency in programming languages widely used in machine learning, such as Python and R</li><li>
Strong understanding of machine learning frameworks (e.g., TensorFlow, PyTorch) as well as experience in model management</li><li>
Experience with cloud platforms (AWS, Azure, Google Cloud) and understanding of scalable architectures</li><li>
Strong experience with monitoring tools and best practices, including setting up automated alerts, dashboards, and logging pipelines for production ML systems</li><li>
Familiarity with observability stacks like Prometheus, Grafana, or similar solutions</li><li>
Excellent problem-solving skills and ability to collaborate effectively within a multi-disciplinary team</li><li>
Strong communication skills, with the ability to articulate complex technical details to non-technical stakeholders</li><li>
English level of minimum B2 (Upper-Intermediate) for effective communication</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>

Movius Interactive

<div><h1 class="jobSectionHeader">Job Title: ML Ops Engineer &ndash; Speech AI &amp; Infrastructure (5&ndash;8 Years)</h1>
<h2 class="jobSectionHeader">Location: Bangalore (India)</h2>
<h2 class="jobSectionHeader">Full-Time | Immediate Joiners Preferred</h2>
<h3 class="jobSectionHeader">Role Summary:</h3>
We are looking for an experienced ML Ops Engineer (5&ndash;8 years) with a strong background in operationalizing AI/ML systems, particularly in speech AI agents integrated into telephony environments. This role bridges AI infrastructure, voice bot deployment, and real-time streaming operations, enabling AI models to function reliably in production use cases such as customer collections, voice-based load bookings, and conversational AI in logistics and telecom.
<h3 class="jobSectionHeader">Key Responsibilities:</h3>
<ul><li>Build, deploy, and maintain real-time speech AI agents for telephony (inbound/outbound) using CPaaS platforms and audio pipelines.</li>
<li>Integrate ASR (Automatic Speech Recognition), TTS (Text-to-Speech), and LLMs with voice bot workflows using WebSocket or RTP streams.</li>
<li>Work closely with backend engineers and AI scientists to deploy scalable ML models into production across Kubernetes, Docker, and cloud-native environments (AWS/GCP).</li>
<li>Set up observability, logging, and monitoring of speech pipelines (latency, dropouts, stream integrity) using Prometheus, Grafana, ELK, etc.</li>
<li>Automate the ML lifecycle and CI/CD for AI models using tools like MLflow, Airflow, or Kubeflow.</li>
<li>Manage streaming latency optimization across ASR, LLM, and TTS chains in low-latency applications like telephony bots.</li>
<li>Ensure fault-tolerant, secure, and compliant deployment of voice-based systems using industry-standard DevOps practices.</li>
</ul><h3 class="jobSectionHeader">Required Skills:</h3>
<ul><li>5&ndash;8 years of experience in ML Ops, AI platform engineering, or DevOps with hands-on ML deployment.</li>
<li>Experience with ASR/TTS model integration (e.g., Whisper, Amazon Polly, Google Speech API).</li>
<li>Hands-on experience deploying AI in telephony environments, with working knowledge of Asterisk, FreeSWITCH, or similar systems.</li>
<li>Solid command over WebSocket, SIP, RTP, or similar streaming protocols for voice integration.</li>
<li>Proficient with cloud services (AWS/GCP/Azure), containers (Docker), orchestration (Kubernetes), and infrastructure as code (Terraform).</li>
<li>Experience with end-to-end CI/CD pipelines, GitOps, and model monitoring (accuracy, drift, performance).</li>
<li>Strong programming in Python and scripting to support infrastructure and integration tasks.</li>
</ul><h3 class="jobSectionHeader">Nice to Have:</h3>
<ul><li>Exposure to CPaaS platforms (e.g., Twilio, Vonage, Kaleyra, Exotel) for voice bot integration.</li>
<li>Familiarity with conversational AI/NLU platforms and agentic AI frameworks.</li>
<li>Prior experience supporting AI agents in collections, logistics/freight, or telecom workflows.</li>
</ul><h3 class="jobSectionHeader">What We Offer:</h3>
<ul><li>Work on next-gen AI voice agents deployed in high-impact customer environments.</li>
<li>Influence platform architecture and deliver cutting-edge infrastructure for real-time ML.</li>
<li>High-ownership, engineering-led culture with strong product alignment and technical mentorship.</li></ul></div>

MLOPS ENGINEER

<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

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