cloud ml 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>
</div><div></div><ul><div><div>Share Vacancy on Facebook</div></div>
<div></div><div><div>Share Vacancy on X</div></div>
<div></div><div><div>Share Vacancy on LinkedIn</div></div>
<div></div><div><div>Share Vacancy on WhatsApp</div></div>
<div></div><div><div>Send Vacancy to a friend</div></div></ul></div></div></div>

ML Ops Engineer (experienced) - Cary, NC

Infosys

<div><h2 class="jobSectionHeader"><b>Job Description:</b></h2><br>
<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><br>
<h2 class="jobSectionHeader"><b>
Key Responsibilities:</b></h2><br>
<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><br>
<h2 class="jobSectionHeader"><b>
Technical Requirements:</b></h2><br>
<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><br>
<h2 class="jobSectionHeader"><b>
Additional Responsibilities:</b></h2><br>
<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><br>
<h2 class="jobSectionHeader"><b>
Preferred Skills:</b></h2>
Technology-&gt;Machine learning-&gt;data science</div>

Machine Learning Engineer

BT Group

<div><div><div><div><div><h1 class="jobSectionHeader"><b>Senior Machine Learning Engineer
</b></h1></div></div></div></div><div><div><div><div>Job Req ID: 52184
</div></div></div></div><div><div><div><div>Posting Date: 15 Oct 2025
</div></div></div></div><div><div><div><div>Function: Data &amp; AI
</div></div></div></div><div><div><div><div>Unit: Digital
</div></div></div></div><div><div><div><div>Location:
RMZ Ecoworld, Devarabeesanahal, Bengaluru, India
</div></div></div></div><div><div><div><div>Salary: Competitive
</div></div></div></div><div></div><div><div><div><div><div><div><div><h2 class="jobSectionHeader"><b>Why this job matters</b></h2>
</div><div><p>
BT has set out on of one of the largest data transformation programmes in the UK in partnership with Google. Our business units have incredibly rich data sets that are evolving rapidly as we look to deliver the next generation of Digital products and services to our customers. It doesn&rsquo;t matter where we look there is not a unit or process that will not benefit from using Data &amp; Analytics, from simple management information reports through to interactive &amp; proactive marketing messages provided to support key business applications through our single version of the truth.</p>
<p>
Key to this transformation is the creation of a data fabric for which BT has selected Ab Initio as its core technology. BT&rsquo;s vision of the data fabric is a self-service technology which supports the safe movement and consolidation of BT&rsquo;s data at scale, through activated meta-data and automated policy enforcement. This role will be responsible for architecting new Data Fabric pattern, triaging new Data Fabric demand and performing assurance for data integration solutions.</p></div></div><div><div><h2 class="jobSectionHeader"><b>
What you&rsquo;ll be doing</b></h2>
</div><div><ul><li>Lead, mentor, and develop you engineering team, fostering a culture of learning and collaboration.</li><li>Architect and build on BT&rsquo;s MLOps stacks for fast, safe, and scalable ML/GenAI delivery with clear FinOps guardrails.</li><li>Design and implement production-grade ML/AI infrastructure, championing reusable patterns and best practices with Data Scientists, support, and engineering teams.</li><li>Embed FinOps, security, and data privacy into every stage of the ML/AI lifecycle.</li><li>Work closely with data scientists, engineers, and stakeholders to accelerate research-to-production using robust engineering practices and AI coding tools.</li><li>Define support strategies for long-term model health, including SLOs, drift monitoring, and feedback loops.</li><li>Lead deployment of LLM and GenAI services on platforms like Amazon Bedrock and Google Vertex AI.</li><li>Design and translate infrastructure for GenAI applications: vector databases, embeddings, retrieval/RAG, model gateways, GPU management, observability, and cost monitoring.</li><li>Promote experiment tracking and model management tools (e.g., Weights &amp; Biases).</li><li>Ensure strong software engineering practices: code review, testing, documentation, and version control.</li></ul></div></div><div><div><h2 class="jobSectionHeader"><b>
Skills and Experience Required</b></h2>
</div><div><ul><li>Bachelor&rsquo;s degree, MSc, or equivalent in Computer Science, Engineering, Mathematics, or related field.</li><li>Professional certifications in AWS, GCP, or Azure (Architect, Engineering, or ML) are highly desirable.</li><li>5+ years in ML/AI engineering, cloud engineering, or MLOps (or 3+ years with exceptional impact).</li><li>Deep expertise in at least one major cloud platform (AWS, GCP, or Azure); knowledge of Vertex AI or equivalent required.</li><li>Proven experience building, debugging, and deploying ML pipelines for large-scale, high-throughput, low-latency applications.</li><li>Production-level fluency managing components in Python, Docker, and deploying ML/AI services (e.g., FastAPI). Supporting skills in SQL and advanced use of Terraform, Pulumi, or AWS CDK.</li><li>Advanced expertise in CI/CD pipelines (GitLab CI, GitHub Actions) and MLOps pipelining services (Kubeflow, TFX, Kedro, or MLflow).</li><li>Practical experience deploying LLMs and other AI models, with understanding of sourcing, performance, quantization, batching, inference service management, metrics, and design trade-offs.</li><li>Demonstrated experience managing FinOps, security, and data privacy in ML/AI systems.</li><li>Proven ability to work directly with data scientists, stakeholders, and as part of Agile squads.</li><li>Experience leading, mentoring, and developing a positive engineering team culture.</li><li>Personal commitment to continuous learning and professional development.</li></ul></div></div><div><div><h2 class="jobSectionHeader"><b>
Our leadership standards</b></h2>
</div><div><p><b>
Looking in:</b><br>
<b>Leading inclusively and Safely</b><br>
I inspire and build trust through self-awareness, honesty and integrity.<br>
<b>Owning outcomes</b><br>
I take the right decisions that benefit the broader organisation.</p>
<p><b>Looking out:</b><br>
<b>Delivering for the customer</b><br>
I execute brilliantly on clear priorities that add value to our customers and the wider business.<br>
<b>Commercially savvy</b><br>
I demonstrate strong commercial focus, bringing an external perspective to decision-making.</p>
<p><b>Looking to the future:</b><br>
<b>Growth mindset</b><br>
I experiment and identify opportunities for growth for both myself and the organisation.<br>
<b>Building for the future</b><br>
I build diverse future-ready teams where all individuals can be at their best.</p></div></div></div><p><b>
About us</b></p>
<p>
BT Group was the world&rsquo;s first telco and our heritage in the sector is unrivalled. As home to several of the UK&rsquo;s most recognised and cherished brands &ndash; BT, EE, Openreach and Plusnet, we have always played a critical role in creating the future, and we have reached an inflection point in the transformation of our business.<br>
<br>
Over the next two years, we will complete the UK&rsquo;s largest and most successful digital infrastructure project &ndash; connecting more than 25 million premises to full fibre broadband. Together with our heavy investment in 5G, we play a central role in revolutionising how people connect with each other.<br>
<br>
While we are through the most capital-intensive phase of our fibre investment, meaning we can reward our shareholders for their commitment and patience, we are absolutely focused on how we organise ourselves in the best way to serve our customers in the years to come. This includes radical simplification of systems, structures, and processes on a huge scale. Together with our application of AI and technology, we are on a path to creating the UK&rsquo;s best telco, reimagining the customer experience and relationship with one of this country&rsquo;s biggest infrastructure companies.<br>
<br>
Change on the scale we will all experience in the coming years is unprecedented. BT Group is committed to being the driving force behind improving connectivity for millions and there has never been a more exciting time to join a company and leadership team with the skills, experience, creativity, and passion to take this company into a new era.</p><br>
<p></p>
<p><b>
A FEW POINTS TO NOTE:</b></p><br>
<p></p>
<p>
Although these roles are listed as full-time, if you&rsquo;re a job share partnership, work reduced hours, or any other way of working flexibly, please still get in touch.</p>
<p>
We will also offer reasonable adjustments for the selection process if required, so please do not hesitate to inform us.</p>
<p><b>
DON'T MEET EVERY SINGLE REQUIREMENT?</b></p>
<p>
Studies have shown that women and people who are disabled, LGBTQ+, neurodiverse or from ethnic minority backgrounds are less likely to apply for jobs unless they meet every single qualification and criteria. We're committed to building a diverse, inclusive, and authentic workplace where everyone can be their best, so if you're excited about this role but your past experience doesn't align perfectly with every requirement on the Job Description, please apply anyway - you may just be the right candidate for this or other roles in our wider team.</p></div></div></div></div></div><p></p>

Senior Machine Learning Engineer

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

NIKE

<div><h2 class="jobSectionHeader"><b>WHO YOU&rsquo;LL WORK WITH</b></h2><p></p><p>
You&rsquo;ll be joining a dynamic, fast-paced Global FPE (Foundational Platforms Engineering) team within Nike. Our mission is to build and scale world-class cloud-native platforms, enabling Nike&rsquo;s data-driven decision-making and intelligent automation capabilities. This role sits right into AI-driven innovation helping to drive cutting-edge advancements in both analytics and intelligent automation.</p><p>
Collaboration and creativity are at our core, and we are passionate about leveraging cloud-scale data platforms and AI-powered automation to transform business</p><p>
operations.</p><p></p><h2 class="jobSectionHeader"><b>
WHO WE ARE LOOKING FOR</b></h2><p></p><p>
We are seeking a Software Engineer who brings deep expertise in Databricks,</p><p>
AWS Services, Cloud Platforms, and AI-driven automation. You are someone who thrives in building scalable, high-performance data platforms to improve efficiency, insights, and user experience.</p><p>
Key Skills &amp; Traits:</p><ul><li><p>
1+ years of production experience in AI/ML model development, deployment, and maintenance</p></li><li><p>
Proven expertise with Large Language Models (LLMs) and NLP tasks</p></li><li><p>
Strong background in data science and cloud-based AI/ML services (Databricks preferred)</p></li><li><p>
Expertise in MLOps/LLMOps for scalable model deployment and management</p></li><li><p>
Advanced programming skills in Python, SQL, and automation frameworks</p></li><li><p>
Worked in Cloud Platforms: Databricks(AI-ML)</p></li><li><p>
MLOps/LLMOps and MLFlow</p></li><li><p>
Passion for leveraging AI to enhance automation, efficiency, and analytics</p></li><li><p>
Strong collaboration, problem-solving, and leadership skills, with the ability to drive initiatives across multiple teams.</p></li></ul><p></p><p><b>
Good to have</b> :</p><ul><li><p>
Data Processing: Pandas, NumPy, Spark.</p></li><li><p>
DevOps: Docker, Kubernetes, DVC(Data Version control)/model monitoring and versioning.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
WHAT YOU&rsquo;LL WORK ON</b></h2><ul><li><p>
As a Software Engineer, you will play a crucial role in shaping, modernizing, and scaling by helping driving AI adoption and automation.</p></li><li><p>
Core AI/ML engineer Responsibilities.</p></li><li><p>
Develop end-to-end ML pipelines with focus on production reliability.</p></li><li><p>
Implement robust testing and validation frameworks for ML models.</p></li><li><p>
Establish best practices for model versioning and reproducibility.</p></li><li><p>
Build and optimize production-grade ML models .</p></li><li><p>
Develop custom NLP solutions for text analysis and processing.</p></li><li><p>
Create automated model evaluation and optimization pipelines.</p></li><li><p>
Manage ML infrastructure on Databricks cloud platform.</p></li><li><p>
Ensure scalability and cost optimization of ML deployments.</p></li><li><p>
Maintain data quality and pipeline efficiency.</p></li><li><p>
Maintain security and compliance implementations for ML systems.</p></li><li><p>
Evangelize AI adoption, helping Nike teams unlock new automation</p></li></ul></div><p></p>

Software Engineer I,ITC

ixceed

<p><b>Role: Senior Python Devops Engineer</b></p><p><b>Location: Chennai</b></p><p><b>Mode: Hybrid</b></p><p><b>Type: Contract</b></p><p><b>Job Description:</b></p><p><b>About the Role:</b></p><p>We are seeking an experienced <b>Senior Python DevOps Engineer</b> with strong expertise in backend development, CI/CD automation, and cloud-based AI/ML environments. The ideal candidate will be responsible for designing, implementing, and maintaining scalable solutions that support AI-driven applications and data workflows across diverse domains.</p><p><b>Key Responsibilities:</b></p><ul><li>Design, develop, and maintain backend services using <b>Python (Flask, FastAPI)</b>.</li><li>Build and manage <b>CI/CD pipelines</b> using <b>Jenkins</b> and <b>GitHub Actions</b>.</li><li>Integrate and optimize databases including <b>Teradata</b> and <b>Snowflake</b>.</li><li>Orchestrate and schedule workflows using <b>Apache Airflow</b>.</li><li>Work with <b>MLflow</b> and <b>Dataiku</b> to support the management of machine learning model lifecycles</li><li>Deploy and manage applications in <b>OpenShift</b> and containerized environments (<b>Docker</b>, <b>Kubernetes</b>).</li><li>Collaborate with AI/ML teams to integrate <b>LLM/GenAI</b> models into production systems.</li><li>Support <b>cloud migration strategies</b> and ensure robust infrastructure design.</li><li>Engage with global, cross-functional teams to deliver high-quality, scalable solutions.</li><li>Contribute to UI development using <b>Streamlit</b> (added advantage).</li></ul><p><b>Required Skills &amp; Experience:</b></p><ul><li><b>5+ years</b> of experience as a <b>Senior Python/DevOps Engineer</b>.</li><li><b>Expert-level proficiency</b> in <b>Python, Flask, and FastAPI</b>.</li><li>Strong experience in <b>DevOps practices</b>, including <b>CI/CD</b>, <b>Kubernetes</b>, and <b>Docker</b>.</li><li>Hands-on experience with <b>GitHub Actions</b> and <b>Jenkins</b>.</li><li>Solid understanding of <b>Teradata</b> and <b>Snowflake</b> databases.</li><li>Experience with <b>Airflow</b>, <b>MLflow</b>, and <b>Dataiku</b>.</li><li>Working knowledge of <b>cloud platforms</b> (AWS, Azure, or GCP).</li><li>Familiarity with <b>AI/ML concepts</b>, <b>LLMs</b>, and <b>Generative AI</b> (at least basic exposure).</li><li><b>Excellent communication skills</b> with the ability to engage stakeholders effectively.</li><li><b>Strong problem-solving</b> and <b>decision-making</b> skills.</li><li>Proven ability to work in a <b>collaborative, global team environment</b>.</li><li>Experience in <b>intercultural teams</b> is highly desirable.</li></ul><p>Job Type: Permanent</p><p>Pay: &#8377;2,500,000.00 - &#8377;3,000,000.00 per year</p><p>Experience:</p><ul><li>Python : 5 years (Required)</li><li>DevOps Engineering: 5 years (Required)</li><li>Flask, Fast API: 3 years (Required)</li><li>Jenkins: 3 years (Required)</li><li>Github Actions: 3 years (Required)</li><li>ML Flow: 3 years (Required)</li><li>Cloud  platforms and migration strategies.: 2 years (Required)</li><li>AI/ML basics(LLM Gen AI): 3 years (Required)</li><li>SQL: 2 years (Required)</li></ul><p>Work Location: In person</p>

Senior Python Devops Engineer

Apple

<div>Are you meticulously organized and highly observant? Join our Information Systems and Technology group and play a vital function on one of two Apple teams: Software and Services and Corporate Functions. From Apple ID to the Apple website to our data centers around the globe, our diverse collection of engineers, designers and creators manage the massive systems and services that so many people rely on every single day! The Applied Machine Learning team has been at the forefront of accelerating digital transformation through machine learning across Apple's enterprise ecosystem. The proven ML Platforms, Solutions, and Services provide a comprehensive suite of capabilities to achieve efficiency, agility, and innovation at Apple scale-serving business-critical needs across Apple&rsquo;s enterprise. We are looking for a talented engineer to join our team to bring passion for infrastructure and distributed systems, to build world-class platforms/products at a very large scale across cloud environments.
<br>
<br>
<b>Description</b><br>
<br>
Embark on a transformative journey as a Software Engineer within Apple's esteemed Applied Machine Learning Team, where you will assume a pivotal role in architecting and orchestrating the high-performance, scalable enterprise platforms that underpin our groundbreaking Data, ML and inferencing platforms. You shall be entrusted with the stewardship of ensuring unparalleled availability, optimal performance, and minimal latency for our high-throughput applications, thereby directly influencing and elevating the customer experience. Your responsibilities will encompass the management of diverse workloads across ML/Data/Inference platforms, coupled with the exploration and evaluation of latest open source technologies and innovative solutions. A proven aptitude for outstanding interpersonal communication and the capacity to collaborate seamlessly across multifaceted business and technical teams are paramount. We are looking for enthusiastic engineers with interest in one of the following areas: &bull; Platform Reliability Engineer &bull; Big Data Engineer &bull; ML Engineer
<br>
<br>
<b>Minimum Qualifications</b><br>
<ul><li>
Bachelor&rsquo;s Degree in Computer Science, Computer Engineering or equivalent.
</li><li>AWS/GCP or Kubernetes Experience
</li><li>Proficient programming knowledge in one of the following areas: Python, Java, or Go Programming and ability to read and explain open source codebase
</li><li>Understanding or exposure in Operating Systems or Networking and Security Principles
</li><li>Relevant Internship experience
</li></ul><br>
<b>Preferred Qualifications</b><br>
<ul><li>
Excellent analytical &amp; problem solving skills
</li><li>Exposure to Data processing and Model Training or FineTuning methodologies
</li><li>Exposure to Spark/Flink and other modern cloud native big data technologies
</li><li>Exposure to Cloud managed services like AWS BedRock/GCP Vertex AI
</li><li>Exposure to various LLM infrastructure like GPUs, TPUs &amp; Inferentia
</li><li>Understanding of Networking concepts on Cloud, like VPCs, DNS, Security Groups, Kubernetes network model
</li>Expertise in Performance tuning JVMs &amp; Operating Systems like Linux<br>
<li>
</li></ul><br>
<br>
Submit CV</div>

Reliability Engineer

Search 10000+ Cloud ml engineer jobs near you this October. New roles added regularly across leading industries. Apply today.