mlops engineer

Indegene

<p></p><div><div><div><div><div><b>Date: </b>8 Oct 2025
</div></div></div></div><div><div><div><div><b>Location:
</b>KA, IN
</div></div></div></div><div><div><div><div><div><div><div><div>Job Description</div>
</div><div><div>
We are a technology-led healthcare solutions provider. We are driven by our purpose to enable healthcare organizations be future ready. We offer accelerated, global growth opportunities for talent that&rsquo;s bold, industrious and nimble. With Indegene, you gain a unique career experience that celebrates entrepreneurship, and is guided by passion, innovation, collaboration and empathy. To explore exciting opportunities at the convergence of healthcare and technology, check out www.careers.indegene.com</div><br>
<div>
What if we told you that you can move to an exciting role in an entrepreneurial organization without the usual risks associated with it?</div><br>
<div>
We understand that you are looking for growth and variety in your career at this point and we would love for you to join us in our journey and grow with us. At Indegene, our roles come with the excitement you require at this stage of your career with the reliability you seek. We hire the best and trust them from day 1 to deliver global impact, handle teams and be responsible for the outcomes while our leaders support and mentor you.</div><br>
<div>
We are a profitable rapidly growing global organization and are scouting for the best talent for this phase of growth. With us, you are at the intersection of two of the most exciting industries of healthcare and technology. We offer global opportunities with fast-track careers while you work with a team that is fuelled by purpose. The combination of this will lead to a truly differentiated experience for you.</div><br>
<div>
If this excites you, then apply below.</div><div><br>
Job Title: MLOps Engineer</div><br>
<div>
Description: We are seeking an experienced MLOps Engineer to join our team and play a key role in deploying, automating, monitoring, and optimizing machine learning solutions. The ideal candidate will have strong experience with Databricks, SQL, Python, PySpark, and CI/CD pipelines, along with hands-on exposure to Jenkins, SonarQube, Jira, and Git.</div><div><br>
You will collaborate with data scientists, data engineers, and DevOps teams to streamline the ML lifecycle &mdash; from model development to production deployment and monitoring.</div><div><br>
Key Responsibilities<br>
<ul><li>Design, implement, and maintain MLOps pipelines for machine learning model deployment and monitoring.</li><li>Collaborate with data scientists to package and deploy ML models in Databricks environments.</li><li>Develop scalable data processing pipelines using PySpark and SQL.</li><li>Implement CI/CD pipelines for ML workflows using Jenkins and ensure code quality with SonarQube.</li><li>Integrate ML workflows with version control systems (Git) and project management tools (Jira).</li><li>Automate data ingestion, feature engineering, model training, evaluation, and deployment processes.</li><li>Monitor deployed models for performance drift, accuracy, and operational issues.</li><li>Troubleshoot, optimize, and refactor ML pipelines for better efficiency and reliability.</li><li>Enforce coding standards, security best practices, and compliance requirements.</li><li>Experience in Lake House monitoring for model monitoring and feature store</li><li>Orchestration of ML jobs jobs in Jenkins</li></ul></div></div></div><div><div><div>
Must Have</div>
</div><div><div>
Required Skills &amp; Qualifications<br>
<ul><li>3+ years of experience as an MLOps Engineer, Data Engineer, or similar role.</li><li>Strong expertise in Databricks for model deployment and data engineering.</li><li>Proficiency in Python and PySpark for data processing and ML workflow automation.</li><li>Solid SQL skills for querying and manipulating structured data.</li><li>Hands-on experience with CI/CD tools like Jenkins.</li><li>Experience with SonarQube for code quality checks.</li><li>Familiarity with Git for version control and Jira for task/project management.</li><li>Understanding of ML model lifecycle, including training, validation, deployment, and monitoring.</li><li>Strong problem-solving skills and ability to work in cross-functional teams.</li></ul></div><div><br>
Preferred Skills<br>
<ul><li>Experience with AWS, Azure, or GCP for cloud-based ML solutions.</li><li>Exposure to MLflow for experiment tracking and model registry.</li><li>Understanding of security best practices in ML pipelines.</li></ul></div></div></div><div><div><div>
Good to have</div>
</div></div><div></div><div><div><div>EQUAL OPPORTUNITY</div>
</div><div>Indegene is proud to be an Equal Employment Employer and is committed to the culture of Inclusion and Diversity. We do not discriminate on the basis of race, religion, sex, colour, age, national origin, pregnancy, sexual orientation, physical ability, or any other characteristics. All employment decisions, from hiring to separation, will be based on business requirements, the candidate&rsquo;s merit and qualification. We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, national origin, gender identity, sexual orientation, disability status, protected veteran status, or any other characteristics.</div></div></div></div></div></div></div></div><p></p>

MLOps Engineer

Capgemini

<div><p><b>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.
</b></p><div><div><div><h2 class="jobSectionHeader"><b>Your Role
</b></h2></div><div><ul><li><b>Design, implement, and maintain end-to-end ML pipelines for model training, evaluation, and deployment
</b></li><li><b>Collaborate with data scientists and software engineers to operationalize ML models, serving frameworks (TensorFlow Serving, TorchServe) and experience with MLOps tools
</b></li><li><b>Develop and maintain CI/CD pipelines for ML workflows
</b></li><li><b>Implement monitoring and logging solutions for ML models, experience with ML model serving frameworks (TensorFlow Serving, TorchServe)
</b></li><li><b>Optimize ML infrastructure for performance, scalability, and cost-efficiency
</b></li></ul></div></div><div><div><h2 class="jobSectionHeader"><b>Your Profile
</b></h2></div><div><ul><li><b>Strong programming skills in Python (5+ years), with experience in ML frameworks; understanding of ML-specific testing and validation techniques
</b></li><li><b>Expertise in containerization technologies (Docker) and orchestration platforms (Kubernetes), Knowledge of data versioning and model versioning techniques
</b></li><li><b>Proficiency in cloud platform (AWS) and their ML-specific services with atleast 2-3 years of experience.
</b></li><li><b>Strong understanding of DevOps practices and tools (GitLab, Artifactory, Gitflow etc.)
</b></li><li><b>Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack) and knowledge of distributed training techniques
</b></li></ul></div></div><div><div><h2 class="jobSectionHeader"><b>What you&rsquo;ll love about working here
</b></h2></div><div><ul><li><b>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
</b></li><li><b>Our focus will be your career growth &amp; professional development to support you in exploring the world of opportunities.
</b></li><li><b>Equip yourself with valuable certifications &amp; training programmes in the latest technologies such as MLOps, Machine Learning
</b></li></ul></div></div></div><p><b>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.</b></p></div>

MLOPS Engineer

Mastercard

<div><p><b>Our Purpose</b></p><p></p><p><i>
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we&rsquo;re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.</i></p><p></p><p><b>
Title and Summary</b></p><p></p>
Senior MLOps Engineer-1<p></p>
Horizontal Data Science Enablement Team within SSO Data Science is looking for a Senior MLOps Engineer who can help solve MLOps problems, manage the Databricks platform for the entire organization, build CI/CD or automation pipelines, and lead best practices.
<br>
<br>
All about you:
<br>
<br>
Assist in the administration, configuration, and maintenance of Databricks clusters and workspaces.
<br>
Monitor Databricks clusters for high workloads or excessive usage costs, and promptly alert relevant stakeholders to address issues impacting overall cluster health.
<br>
Implement and manage security protocols, including access controls and data encryption, to safeguard sensitive information in adherence with Mastercard standards.
<br>
Facilitate the integration of various data sources into Databricks, ensuring seamless data flow and consistency.
<br>
Identify and resolve issues related to Databricks infrastructure, providing timely support to users and stakeholders.
<br>
Assist in development of MLOps solutions, namely within the scope of, but not limited to:
<br>
Model monitoring
<br>
Feature catalog/store
<br>
Model lineage maintenance
<br>
CI/CD pipelines to gatekeep model lifecycle from development to production
<br>
Maintain services once they are live by measuring and monitoring availability, latency and overall system health.
<br>
<br>
What experience you need:
<br>
<br>
Master&rsquo;s degree in computer science, software engineering, or a similar field.
<br>
Strong experience with Databricks and its management of roles and resources
<br>
Experience with MLOps solutions like MLFlow
<br>
Experience with performing data analysis, data observability, data ingestion and data integration.
<br>
2+ DevOps, SRE, or general systems engineering experience.
<br>
2+ years of hands-on experience in industry standard CI/CD tools like Git/BitBucket, Jenkins, Maven, Artifactory, and Chef.
<br>
Strong coding ability in Python or other languages like Java, and C++, plus a solid grasp of SQL fundamentals
<br>
Systematic problem-solving approach, coupled with strong communication skills
<br>
What could set you apart
<br>
<ul><li>SQL tuning experience.
</li><li>Strong automation experience
</li><li>Ability to operate in a 24x7 environment encompassing global time zones</li></ul><p></p><p><b>
Corporate Security Responsibility</b></p><p><br>
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:</p><ul><li><p>
Abide by Mastercard&rsquo;s security policies and practices;</p></li><li><p>
Ensure the confidentiality and integrity of the information being accessed;</p></li><li><p>
Report any suspected information security violation or breach, and</p></li><li><p>
Complete all periodic mandatory security trainings in accordance with Mastercard&rsquo;s guidelines.</p></li></ul></div><p></p>

Senior MLOps Engineer-1

SALLA

<div><p>Salla is on the lookout for a talented Senior MLOps Engineer to help streamline our machine learning lifecycle by implementing best practices and innovative solutions. In this role, you will work closely with data scientists, software engineers, and stakeholders to deploy robust machine learning models and maintain efficient operations.</p><h3 class="jobSectionHeader"><b>
Responsibilities:</b></h3><ul>
<li>Design, build, and maintain scalable MLOps pipelines that foster collaboration between data scientists and engineering teams.</li>
<li>Implement and manage workflows for model training, validation, deployment, and monitoring.</li>
<li>Utilize cloud-based platforms (AWS, GCP, or Azure) to provision and manage machine learning resources.</li>
<li>Develop tools and frameworks that assist in continuous integration and deployment of machine learning models.</li>
<li>Collaborate with data scientists to understand model requirements and assist in feature engineering and selection.</li>
<li>Monitor model performance in production, identify issues, and provide recommendations for model optimization.</li>
<li>Establish best practices for versioning, testing, and documenting machine learning models.</li>
<li>Stay updated with the latest developments in MLOps tools and methodologies.</li>
<li>Strong communication skills to relay technical concepts to non-technical stakeholders.</li>
<li>Excellent problem-solving skills and a proactive approach to addressing challenges.</li>
</ul><p><b>Requirements</b></p><ul><li><ul>
<li>5+ years of experience in MLOps, ML Infrastructure, or related engineering roles.</li>
<li>Demonstrated experience deploying machine learning models into production.</li>
<li>Strong programming skills in <b>Python</b> and familiarity with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).</li>
<li>Proficiency with <b>containerization and orchestration</b> (Docker, Kubernetes).</li>
<li>Experience with <b>cloud ML platforms</b> (AWS, GCP, or Azure).</li>
<li>Familiarity with <b>workflow orchestration</b> (Airflow, Prefect, Mage, or equivalents).</li>
<li>Understanding of CI/CD automation for ML workloads.</li>
<li>Working knowledge of <b>DevOps concepts</b> (infrastructure-as-code, logging/monitoring, networking basics).</li>
<li>Experience working on recommendation systems</li>
</ul></li></ul><p><b>Benefits</b></p><ul>
<li>Comprehensive Training &amp; Development programs.</li>
<li>Performance-based Bonus incentives.</li>
<li>Flexible Work From Home options.</li></ul></div>

Senior ML Engineer,

HR Force International

We are seeking an experienced and innovative DevOps Engineer / Linux Administrator for our DevOps operations. This role focuses on managing a comprehensive ecosystem, including SRE, DevOps, DevSecOps, MLOps, infrastructure, data centers, and custom server management. The ideal candidate will bring strong leadership skills, oversee team operations, implement robust automation, maintain secure access controls, manage Hetzner and other hosting platforms, and ensure the scalability, reliability, and cost-efficiency of our systems.
<br><br>
<b>Roles and Responsibilities:</b><br>
<b>Linux Administration:</b> Administer and manage Linux-based custom servers, including bare-metal and virtualized infrastructures like Proxmox and VMware.
<br><b>Server Monitoring:</b> Grafana, ELK, Nagios, SNMP, Cloud watch ect
<br><b>Security Management:</b> Implement secure access controls using IAM policies, SSH key management, and VPN solutions such as OpenVPN and WireGuard.
<br><b>Clouds:</b> AWS, GCP, Azure, Hetzneter, OVH CLoud
<br><b>Backup and Recovery:</b> Develop and maintain server backups and disaster recovery plans using Bacula, Veeam, or rsync.
<br><b>Automation:</b> Employ tools like Ansible for automating server configuration, updates, and patch management.
<br><b>Performance Optimization:</b> Proactively monitor and tune system performance using Prometheus, Grafana, and the ELK Stack.
<br><b>Cost Optimization:</b> Analyze and optimize infrastructure costs, ensuring budget efficiency for data centers like Hetzner, DigitalOcean, Linode, and OVH.
<br><br>
<b>Requirements:</b><br>
Bachelor’s or Master’s degree in Computer Science, IT, or a related field.
<br><ul>
<li>2-4 years of experience in Linux system administration, DevOps, or infrastructure management.</li>
<li>Proven 3+ years of leadership experience in managing and guiding technical teams.</li>
<li>Hands-on experience with managing Hetzner and other data center platforms.</li>
<li>Proficiency in automation and configuration management tools (Ansible, Puppet, or Chef).</li>
<li>Advanced expertise in CI/CD pipelines and tools (Jenkins, GitLab CI, or Bamboo).</li>
<li>Deep understanding of cloud services and virtualization platforms (AWS, Azure, VMware).</li>
<li>Strong scripting skills in Bash, Python, or similar languages.</li>
<li>Experience with containerization and orchestration (Docker, Kubernetes).</li>
<li>Knowledge of monitoring and alerting tools (Prometheus, Grafana, Nagios).</li>
<li>Familiarity with security practices, including DevSecOps and IAM.</li>
</ul>
Experience with managing hybrid environments across cloud platforms.
<br><ul>
<li>Advanced knowledge of network security and VPN setups for data centers.</li>
<li>Certifications such as RHCE, AWS Certified DevOps Engineer, or Kubernetes Certified Administrator (CKA).</li>
<li>Experience with distributed systems and microservices architecture.</li>
<li>Familiarity with Hetzner’s automation and cost management tools.</li>
</ul>
Good to Have
<br><br>
<ul>
<li>Exposure to MLOps and related tools.</li>
<li>Experience with hybrid cloud and edge computing solutions.</li>
<li>Familiarity with advanced access control solutions (Okta, Keycloak).</li>
<li>Understanding of data center cooling, power management, and hardware optimization.</li>
<li>Knowledge of custom server administration tools like WHMCS for client management and billing.</li>
</ul>


DevOps Engineer (Linux & Cloud Infrastructure)

Amgen

<p></p><div><div><div><p>ABOUT AMGEN</p></div><div><p>
Amgen harnesses the best of biology and technology to fight the world&rsquo;s toughest diseases, and make people&rsquo;s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what&rsquo;s known today.</p></div><p></p><div><p><br>
ABOUT THE ROLE</p></div><div><p>
Role Description:</p></div><div><p>
We are seeking a highly skilled Machine Learning Engineer with a strong MLOps background to join our team. You will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines.</p></div><div><p>
Roles &amp; Responsibilities:</p></div><div><ul><li><p>
Collaborate with data scientists to develop, train, and evaluate machine learning models.</p></li></ul></div><div><ul><li><p>
Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring.</p></li></ul></div><div><ul><li><p>
Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment.</p></li></ul></div><div><ul><li><p>
Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency.</p></li></ul></div><div><ul><li><p>
Develop and implement monitoring systems to track model performance and identify issues.</p></li></ul></div><div><ul><li><p>
Conduct A/B testing and experimentation to optimize model performance.</p></li></ul></div><div><ul><li><p>
Work closely with data scientists, engineers, and product teams to deliver ML solutions.</p></li></ul></div></div><div><div><ul><li><p>
Stay updated with the latest trends and advancements</p></li></ul></div><p></p><div><p><br>
Must-Have Skills:</p></div><div><ul><li><p>
Strong foundation in machine learning algorithms and techniques</p></li></ul></div><div><ul><li><p>
Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD)</p></li></ul></div><div><ul><li><p>
Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)</p></li></ul></div><div><ul><li><p>
Outstanding analytical and problem-solving skills; Ability to learn quickly; Excellent communication and interpersonal skills</p></li></ul></div><p></p><div><p><br>
Good-to-Have Skills:</p></div><div><ul><li><p>
Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing</p></li></ul></div><div><ul><li><p>
Experience with data engineering and pipeline development</p></li></ul></div><div><ul><li><p>
Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification</p></li></ul></div><div><ul><li><p>
Knowledge of NLP techniques for text analysis and sentiment analysis</p></li></ul></div><div><ul><li><p>
Experience in analyzing time-series data for forecasting and trend analysis</p></li></ul></div><div><ul><li><p>
Familiar with AWS, Azure, or Google Cloud;</p></li></ul></div><div><ul><li><p>
Familiar with Databricks platform for data analytics and MLOps</p></li></ul></div><p></p><div><p><br>
Education and Professional Certifications</p></div></div><div><div><ul><li><p>
Master&rsquo;s / Degree degree with 8 -12 years of experience in Computer Science, IT or related field</p></li></ul></div><div><p>
Soft Skills:</p></div><div><ul><li><p>
Excellent analytical and troubleshooting skills.</p></li></ul></div><div><ul><li><p>
Strong verbal and written communication skills</p></li></ul></div><div><ul><li><p>
Ability to work effectively with global, virtual teams</p></li></ul></div><div><ul><li><p>
High degree of initiative and self-motivation.</p></li></ul></div><div><ul><li><p>
Ability to manage multiple priorities successfully.</p></li></ul></div><div><ul><li><p>
Team-oriented, with a focus on achieving team goals.</p></li></ul></div><div><ul><li><p>
Ability to learn quickly, be organized and detail oriented.</p></li></ul></div><div><ul><li><p>
Strong presentation and public speaking skills.</p></li></ul></div><p></p><div><p><br>
EQUAL OPPORTUNITY STATEMENT</p></div><div><p>
Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.</p></div><div><p>
We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.</p></div></div></div><p></p>

Sr Machine Learning Engineer

Nike

<div>
 <strong>
  Who You&rsquo;ll Work With
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 This role sits right into AI-driven innovation helping to drive cutting-edge advancements in both analytics and intelligent automation.
 <br/>
 <br/>
 Collaboration and creativity are at our core, and we are passionate about leveraging cloud-scale data platforms and AI-powered automation to transform business operations.
 <br/>
 <br/>
 <strong>
  Who We Are Looking For
  <br/>
  <br/>
 </strong>
 We are seeking a Software Engineer who brings deep expertise in Databricks, 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.
 <br/>
 <br/>
 <strong>
  Key Skills &amp; Traits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   2-5 years of production experience in AI/ML model development, deployment, and maintenance
  </li>
  <li>
   Proven expertise with Large Language Models (LLMs) and NLP tasks
  </li>
  <li>
   Strong background in data science and cloud-based AI/ML services (Databricks preferred)
  </li>
  <li>
   Expertise in MLOps/LLMOps for scalable model deployment and management
  </li>
  <li>
   Advanced programming skills in Python, SQL, and automation frameworks.
  </li>
  <li>
   Hand on experience in Machine Learning: Supervised and unsupervised learning, model building, evaluation, and optimizations.
  </li>
  <li>
   Hand on experience in Deep Learning: Neural networks, CNNs, RNNs, LSTMs, transformers, and LLMs ; LLM fine-tuning and deployment
  </li>
  <li>
   Completed projects in Natural Language Processing (NLP): Text pre-processing, tokenization, embeddings, sentiment analysis, named entity recognition (NER), anomaly detection
  </li>
  <li>
   Frameworks and Libraries: PyTorch, Keras, Scikit-learn, Hugging Face Transformers.
  </li>
  <li>
   Worked in Cloud Platforms: Databricks(AI-ML) - preferred / AWS (SageMaker)
  </li>
  <li>
   MLOps/LLMOps
  </li>
  <li>
   Passion for leveraging AI to enhance automation, efficiency, and analytics
  </li>
  <li>
   Strong collaboration, problem-solving, and leadership skills, with the ability to drive initiatives across multiple teams.
  </li>
  <li>
   Good to have :
  </li>
  <ul>
   <li>
    Data Processing: Pandas, NumPy, Spark.
   </li>
   <li>
    DevOps: Docker, Kubernetes,DVC(Data Version control)/model monitoring and versioning.
    <br/>
   </li>
  </ul>
 </ul>
 <strong>
  What You&rsquo;ll Work On
  <br/>
  <br/>
 </strong>
 As a Software Engineer, you will play a crucial role in shaping, modernizing, and scaling by helping driving AI adoption and automation.
 <br/>
 <br/>
 <strong>
  Core AI/ML Engineer Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop end-to-end ML pipelines with focus on production reliability.
  </li>
  <li>
   Implement robust testing and validation frameworks for ML models.
  </li>
  <li>
   Establish best practices for model versioning and reproducibility.
  </li>
  <li>
   Build and optimize production-grade ML models .
  </li>
  <li>
   Develop custom NLP solutions for text analysis and processing.
  </li>
  <li>
   Create automated model evaluation and optimization pipelines.
  </li>
  <li>
   Manage ML infrastructure on Databricks cloud platform.
  </li>
  <li>
   Ensure scalability and cost optimization of ML deployments.
  </li>
  <li>
   Maintain data quality and pipeline efficiency.
  </li>
  <li>
   Maintain security and compliance implementations for ML systems.
  </li>
  <li>
   Evangelize AI adoption, helping Nike teams unlock new automation opportunities.
  </li>
 </ul>
</div>


Software Engineer II, ITC

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