ml systems engineer

Jeeny

<div>
 <strong>
  About Jeeny:
  <br/>
  <br/>
 </strong>
 Jeeny is a leading ride-hailing platform that strives to revolutionize daily commuting and transportation. Our app connects users with their preferred modes of transportation, making mobility accessible, convenient, and affordable for all.
 <br/>
 <br/>
 We are a joint venture between MEIG (Middle East Internet Group), Rocket Internet, and IMENA. Since our inception, we have grown exponentially and currently operate in Saudi Arabia and Jordan.
 <br/>
 <br/>
 At Jeeny, we value innovation, teamwork, and a passion for delivering exceptional user experiences. Join us in our mission to transform the transportation landscape.
 <br/>
 <br/>
 <strong>
  About the Role:
  <br/>
  <br/>
 </strong>
 We are looking for an
 <strong>
  ML Systems Engineer
 </strong>
 to build the services, interfaces, and automation required to reliably operate ML-powered features in production. This role is focused on transforming data science models into complete production systems, including APIs, feature pipelines, monitoring dashboards, and operational tooling.
 <br/>
 <br/>
 The ideal candidate will serve as the bridge between
 <strong>
  Data Science, QA, and DevOps
 </strong>
 , ensuring machine learning models are not only accurate, but also deployable, observable, scalable, and maintainable.
 <br/>
 <br/>
 <strong>
  Responsibilities:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, build, and maintain production-ready systems for deploying machine learning models.
  </li>
  <li>
   Develop and manage APIs and backend services that power ML-driven features.
  </li>
  <li>
   Build and maintain feature pipelines to support model training and inference workflows.
  </li>
  <li>
   Create monitoring dashboards and observability tools to track model performance and system health.
  </li>
  <li>
   Automate ML deployment workflows and operational processes to improve reliability and efficiency.
  </li>
  <li>
   Collaborate closely with Data Science, QA, and DevOps teams to ensure smooth model integration and deployment.
  </li>
  <li>
   Improve system scalability, performance, and maintainability of ML-powered applications.
  </li>
  <li>
   Troubleshoot and resolve issues related to production ML systems and deployment pipelines.
  </li>
  <li>
   Implement best practices for versioning, testing, monitoring, and maintaining ML services
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
  </li>
  <li>
   3+ years of experience in backend engineering, ML systems, or MLOps.
  </li>
  <li>
   Strong experience with Python and backend frameworks
  </li>
  <li>
   Experience building and maintaining APIs and microservices.
  </li>
  <li>
   Familiarity with ML deployment workflows and model serving frameworks.
  </li>
  <li>
   Experience with data pipelines and workflow orchestration tools.
  </li>
  <li>
   Strong understanding of cloud platforms
  </li>
  <li>
   Experience with containerization and orchestration tools (Docker, Kubernetes).
  </li>
  <li>
   Knowledge of monitoring and observability tools for production systems.
  </li>
  <li>
   Strong problem-solving skills and ability to work cross-functionally
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 <strong>
  What we offer:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Market Competitive Salary 💰 Hit the ground running with a salary that reflects your worth in today's market
  </li>
  <li>
   Learn &amp; Grow 📚 Level up with real-world projects, cross-functional job rotations, hands-on mentorship, and expert-led sessions tailored to your growth
  </li>
  <li>
   International Exposure 🌍 Collaborate across borders with teams in KSA, Jordan, Pakistan, and UAE&mdash;experience a global career from day one
  </li>
  <li>
   Health Insurance 🏥 Full health coverage so you can focus on your goals with peace of mind
  </li>
  <li>
   OPD Coverage 🏥 Outpatient visits? We've got that covered for you
  </li>
  <li>
   End of Service Benefit 💼 Loyalty pays off, long-term service comes with financial rewards
  </li>
  <li>
   Dollar Adjustment Allowance 💲 With our dollar adjustment allowance, you can stay ahead of inflation. You're protected against currency fluctuations, so your compensation stays consistent and fair
  </li>
  <li>
   Internet Allowance 🌐 Work, stream, and stay in the loop with monthly internet support, whether you're learning, working, or just vibing
  </li>
  <li>
   Learning &amp; Development Allowance 🎓 Get a yearly budget for certifications, courses, or training&mdash;because investing in you is a no-brainer
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Company Culture
  <br/>
  <br/>
 </strong>
 Jeeny is an equal opportunity employer. We are committed to providing a workplace where all aspects of employment are solely based on merit. We value diversity and absolutely do not discriminate in any form based on race, color, ethnicity, nationality, religion, gender, age, or mental or physical disability.
</div>


ML Systems Engineer

Encora Inc.

<div>
 We are seeking an
 <strong>
  AI/ML Engineer &ndash; Agents
 </strong>
 to help build the core intelligence layer of our AI-powered MarTech and AdTech platform. This role will focus on designing, developing, and deploying
 <strong>
  agentic AI systems
 </strong>
 ,
 <strong>
  LLM-powered applications
 </strong>
 , and
 <strong>
  real-time inference pipelines
 </strong>
 that drive intelligent automation, personalization, and decision-making at scale.
 <br/>
 <br/>
 This is a high-impact, hands-on engineering role for someone who thrives in fast-moving environments and wants to help shape next-generation AI products from the ground up.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and deploy agentic AI systems using frameworks such as LangGraph, AutoGen, CrewAI, or similar.
  </li>
  <li>
   Build and scale LLM/GenAI applications for MarTech and AdTech use cases, including content generation, campaign optimization, audience segmentation, personalization, and workflow automation.
  </li>
  <li>
   Fine-tune and optimize LLMs/SLMs for domain-specific tasks such as classification, extraction, recommendation, and intent understanding.
  </li>
  <li>
   Develop and manage training and inference pipelines for production-scale ML systems.
  </li>
  <li>
   Build scalable infrastructure for real-time and batch inference, experimentation, and deployment.
  </li>
  <li>
   Implement best practices for evaluation, A/B testing, model monitoring, and continuous improvement.
  </li>
  <li>
   Partner closely with product, data, and engineering teams to turn prototypes and research into production-ready AI services.
  </li>
  <li>
   Rapidly prototype and apply emerging research to practical product use cases.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   <strong>
    3+ years
   </strong>
   of experience in AI/ML engineering, machine learning, or applied NLP roles.
  </li>
  <li>
   Master&rsquo;s degree in Computer Science, Engineering, or a related field required; PhD preferred.
  </li>
  <li>
   Hands-on experience with agent-based AI frameworks such as LangGraph, AutoGen, CrewAI, or similar.
  </li>
  <li>
   Strong expertise in deep learning and natural language processing using frameworks such as PyTorch or TensorFlow.
  </li>
  <li>
   Experience fine-tuning and deploying foundation models such as LLaMA, Mistral, or similar.
  </li>
  <li>
   Strong experience with Hugging Face, LoRA, PEFT, and modern fine-tuning workflows.
  </li>
  <li>
   Experience with RAG pipelines, vector databases, semantic search, and embedding optimization tools such as FAISS, Pinecone, or PGVector.
  </li>
  <li>
   Experience deploying ML systems in cloud environments such as AWS, GCP, or Azure.
  </li>
  <li>
   Strong software engineering skills in Python, APIs, microservices, and containerized environments such as Docker and Kubernetes.
  </li>
  <li>
   Solid understanding of GPU optimization, distributed training, and inference performance tuning.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience in MarTech, AdTech, personalization, targeting, or attribution systems.
  </li>
  <li>
   Experience with real-time decisioning or ad-serving systems.
  </li>
  <li>
   Contributions to open-source AI/LLM frameworks or published research.
  </li>
  <li>
   Prior experience in a startup or high-growth environment.
  </li>
 </ul>
</div>


AI/ML Engineer

Agoda

<div>
 <strong>
  About Agoda
  <br/>
  <br/>
 </strong>
 At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
 <br/>
 <br/>
 Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
 <br/>
 <br/>
 No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you&rsquo;re ready to begin your best journey and help build travel for the world, join us.
 <br/>
 <br/>
 Agoda is an online travel booking platform for accommodation, flights, and more. We build and deploy cutting edge technology that connects travelers with more than 2.5 million accommodations globally. Based in Asia and part of Booking Holdings, our 4,000+ talents coming from 90+ different nationalities foster a work environment rich in diversity, creativity, and collaboration. We innovate through a culture of experimentation and ownership, enabling our customers to experience the world.
 <br/>
 <br/>
 <strong>
  Get to Know Our Team
  <br/>
  <br/>
 </strong>
 The Engineering department oversees all Agoda&rsquo;s ML and software related requirements. Our goal is to enable and increase Agoda&rsquo;s business through creative approaches and the implementation of powerful resources such as operational and analytical databases, ML driven solutions, queue systems and data monitoring tools. We hire the brightest minds from around the world to take on this challenge and equip them with the knowledge and tools that contribute to their personal growth and success while supporting our company&rsquo;s culture of diversity and experimentation. The role the engineering team plays at Agoda is critical as business users, product managers, and many others rely on us to empower their decision making. We are equally dedicated to our customers by improving their search experience with faster results and protecting them from any fraudulent activities. Data is interesting only when you have enough of it, and we have plenty. This is what drives up the challenge as part of the ML engineering squad, but also the reward. We work across structured and non-structured data at scale. For example, our current ML models process millions of images every day to try and enhance the experience that our users get from our app.
 <br/>
 <br/>
 <strong>
  Why Agoda Engineering Team (ML role)?
  <br/>
  <br/>
 </strong>
 Our engineering teams are at the intersection of business analytics, ml engineering, data warehousing and software engineering. Our job involves dealing with distributed systems, stream processing, ml modeling and computation at tens of PB Scale. We focus on software engineering related to data replication, storage, centralized computation, and Data API&rsquo;s. By providing our users with ML products/tools, shared frameworks, and ML services, we enable our company to validate strategic decisions, make smarter choices, and react to the fast-changing world. We are a small but passionate team with people from different nationalities working together on a single goal.
 <br/>
 <br/>
 <strong>
  This role is based in Gurgaon, India.
  <br/>
  <br/>
 </strong>
 <strong>
  In this Role, you will get to:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Lead the team technically in improving scalability, stability, accuracy, speed and efficiency of our existing ML systems and processes.
  </li>
  <li>
   Build, administer and scale ML processing pipelines.
  </li>
  <li>
   Be comfortable navigating the following technology stack: Python3, Pyspark, scripting (Bash/Python), Hadoop, SQL, S3 etc.
  </li>
  <li>
   Should be able to understand internals of ML models such as Random Forest, CNN, Regression models, etc
  </li>
  <li>
   Design, build, test and deploy new libraries, frameworks or full systems for our core systems while keeping to the highest standards of testing and code quality.
  </li>
  <li>
   Work with experienced engineers and product owners to identify and build tools to automate many large-scale data management / analysis tasks.
  </li>
  <li>
   We believe in end-to-end ownership; this role will involve taking ML models to production at a scale.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What You&rsquo;ll need to Succeed:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s degree in computer science /information systems/engineering/related field
  </li>
  <li>
   8+ years of experience in software engineering with a minimum of 4+ years in ML
  </li>
  <li>
   Good experience in Pyspark
  </li>
  <li>
   Expert level understanding of Python with design patterns and object-oriented programming.
  </li>
  <li>
   Experience debugging and reasoning about production issues is desirable.
  </li>
  <li>
   A good understanding of data architecture principles preferred.
  </li>
  <li>
   Any other experience with Big Data technologies / tools
  </li>
  <li>
   SQL experience
  </li>
  <li>
   Analytical problem-solving capabilities &amp; experience.
  </li>
  <li>
   Systems administration skills in Linux
  </li>
  <li>
   A strong engineering driven mindset will be required to succeed in this role.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  It&rsquo;s great if you have:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Good understanding of Hadoop ecosystems
  </li>
  <li>
   Experience working with Open-source products
  </li>
  <li>
   Experience with Scala development
  </li>
  <li>
   Working in an agile environment using test driven methodologies
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Hybrid Working Model
  </li>
  <li>
   WFH Set Up Allowance
  </li>
  <li>
   30 Days of Remote Working from anywhere globally every year
  </li>
  <li>
   Employee discount for accommodation globally
  </li>
  <li>
   Global team of 90+ nationalities
  </li>
  <li>
   40+ offices and 25+ countries
  </li>
  <li>
   Annual CSR / Volunteer Time off
  </li>
  <li>
   Benevity Subscription for employee donations
  </li>
  <li>
   Volunteering opportunities globally
  </li>
  <li>
   Free Headspace subscription
  </li>
  <li>
   Free Odilo &amp; Udemy subscriptions
  </li>
  <li>
   Access to Employee Assistance Program (third party for personal and workplace support)
  </li>
  <li>
   Enhanced Parental Leave
  </li>
  <li>
   Life, TPD &amp; Accident Insurance
   <br/>
   <br/>
  </li>
 </ul>
 #telaviv #jerusalem #IT #ENG #4 #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #philadelphia #dallas #houston #austin #seattle #sydney #melbourne #perth #toronto #vancouver #montreal #prague #Brno #Ostrava #cairo #alexandria #giza #estonia #paris #berlin #munich #hamburg #stuttgart #cologne #frankfurt #budapest #bali #dublin #telaviv #milan #rome #venice #florence #naples #turin #palermo #bologna #osaka #malta #amsterdam #oslo #warsaw #krakow #alrayyan #riyadh #jeddah #mecca #medina #singapore #seoul #barcelona #madrid #stockholm #zurich #taipei #tainan #taichung #kaohsiung #bangkok #Phuket #istanbul #london #manchester  #edinburgh #hcmc #hanoi #lodz #wroclaw #poznan #katowice #rio #salvador #newdelhi #bangalore #bandung #yokohama #nagoya #okinawa #fukuoka #jerusalem #IT #4 #bangalore #delhi #hyderabad #pune #singapore #beijing #shanghai #shenzhen #tokyo #seoul #hongkong #taipei #kualalumpur #jakarta #hochiminh #hochiminhcity #manila #instanbul #makati #dubai #riyadh #gurgaon #noida
 <br/>
 <br/>
 Please review our Hiring Process Guidelines before your interview &mdash; click here to learn how interviewing at Agoda works.
 <br/>
 <br/>
 <strong>
  Discover More About Working At Agoda
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Agoda Careers https://careersatagoda.com
  </li>
  <li>
   Facebook https://www.facebook.com/agodacareers/
  </li>
  <li>
   LinkedIn https://www.linkedin.com/company/agoda
  </li>
  <li>
   YouTube https://www.youtube.com/agodalife
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Equal Opportunity Employer
  <br/>
  <br/>
 </strong>
 At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person&rsquo;s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
 <br/>
 <br/>
 We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.
 <br/>
 <br/>
 <strong>
  Disclaimer
  <br/>
  <br/>
 </strong>
 We do not accept any terms or conditions, nor do we recognize any agency&rsquo;s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.
 <br/>
 <br/>
</div>


Staff Machine Learning Engineer (India based, relocation provided)

Texas Instruments

<p></p><div><div><div><div><div><div><div><div><div><div><div><div><b>Change the world. Love your job.</b></div><p>
Texas Instruments is transforming semiconductor manufacturing through AI. This role sits within the Smart Manufacturing Automation (SMA). organization You will design, build, and operate the agentic AI infrastructure that powers factory intelligence across TI's global fab and assembly/test operations to connect large language models to live manufacturing data systems and enabling rapid decision support at scale.</p><p><b>
What You'll Do</b></p><ul><li><div>
Architect and deliver multi-agent AI systems using the A2A (Agent-to-Agent) protocol, including orchestrator and sub-agent topologies that span multiple factory data sources.</div></li><li><div>
Build and maintain MCP (Model Context Protocol) servers in Python, containerized with Docker and deployed on VMs and Kubernetes clusters; register agents and MCP servers.</div></li><li><div>
Integrate LLM inference into factory workflows; manage LiteLLM project credentials, budgets, and routing configurations.</div></li><li><div>
Develop agent tools that query manufacturing databases (MES, FDC, APC, OEE, etc.) and expose clean interfaces for downstream AI consumption.</div></li><li><div>
Design, evolve, and influence the Agent Delivery Framework.</div></li><li><div>
Establish and document agentic software development best practices; create reusable agent templates adopted across business teams.</div></li><li><div>
Build and maintain Knowledge Graph and RAG systems (Neo4j, Vectara) to enable document and parametric data retrieval across thousands of manufacturing documents and records.</div></li><li><div>
Collaborate with multiple departments, domain architects, and factory engineers to identify high ROI agent use cases, prioritize delivery, and ensure agents meet security and authentication requirements.</div></li><li><div>
Present architecture roadmaps and live agent demos to peers and senior manufacturing leadership.</div></li><li><div>
Contribute to cross-domain AI access and guardrails governance strategy.</div></li></ul></div>
</div></div></div></div></div></div><div></div><div><div><div><div><div><div><p>QUALIFICATIONS</p>
<div><div><b>Minimum Qualifications:</b></div>
<ul>
<li><div>Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or a related technical field.</div></li>
<li><div>4+ years of software engineering experience, with at least 2 years focused on AI/ML systems or LLM application development.</div></li>
<li><div>Proficiency in Python and experience containerizing applications with Docker.</div></li>
<li><div>Hands-on experience building or integrating with REST API backends and asynchronous service architectures.</div></li>
<li><div>Strong communication skills &mdash; able to translate complex AI architecture decisions for non-technical manufacturing stakeholders.</div></li></ul><br>
<p></p>
<p><b>
Preferred Qualifications:</b></p>
<ul>
<li><div>Experience with multi-agent AI frameworks, agent orchestration patterns, or the MCP (Model Context Protocol) specification.</div></li>
<li><div>Familiarity with LiteLLM, Open Web UI, or similar LLM proxy/routing platforms.</div></li>
<li><div>Experience deploying workloads on Kubernetes (K8s) or cloud-adjacent enterprise platforms.</div></li>
<li><div>Working knowledge of graph databases (Neo4j) and vector search systems (Vectara, pgvector, or equivalent).</div></li>
<li><div>Prior exposure to semiconductor or discrete manufacturing data systems (MES, FDC, SPC, SCADA, APC) is a strong plus.</div></li>
<li><div>Experience with workflow automation tools (e.g. Airflow) and CI/CD pipelines (Bitbucket, Jenkins, or equivalent).</div></li>
<li><div>Master's degree or equivalent industrial AI research experience.</div></li>
</ul></div>
</div></div></div></div></div></div><div></div><div><div><div><div><div><div><p>ABOUT US</p>
<div><div><div><b>Why TI?</b>
</div><div><ul><li>Engineer your future. We empower our employees to truly own their career and development. Come collaborate with some of the smartest people in the world to shape the future of electronics.</li>
<li>We're different by design. Diverse backgrounds and perspectives are what push innovation forward and what make TI stronger. We value each and every voice, and look forward to hearing yours. Meet the people of TI</li>
<li>Benefits that benefit you. We offer competitive pay and benefits designed to help you and your family live your best life. Your well-being is important to us.</li><br>
</ul></div><p></p><br>
<div><p><b>About Texas Instruments</b>
</p><p>Texas Instruments Incorporated (Nasdaq: TXN) is a global semiconductor company that designs, manufactures and sells analog and embedded processing chips for markets such as industrial, automotive, data center, personal electronics and communications equipment. At our core, we have a passion to create a better world by making electronics more affordable through semiconductors. This passion is alive today as each generation of innovation builds upon the last to make our technology more reliable, more affordable and lower power, making it possible for semiconductors to go into electronics everywhere. Learn more at TI.com.<br>
</p><p></p><br>
<div><div>Texas Instruments is an equal opportunity employer and supports a diverse, inclusive work environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, creed, disability, genetic information, national origin, gender, gender identity and expression, age, sexual orientation, marital status, veteran status, or any other characteristic protected by federal, state, or local laws.<br>
</div><p></p><br>
<p>If you are interested in this position, please apply to this requisition.
</p></div></div></div></div></div></div></div></div></div></div><p></p><div><div><div><div><div><div><div>TI does not make recruiting or hiring decisions based on citizenship, immigration status or national origin. However, if TI determines that information access or export control restrictions based upon applicable laws and regulations would prohibit you from working in this position without first obtaining an export license, TI expressly reserves the right not to seek such a license for you and either offer you a different position that does not require an export license or decline to move forward with your employment.</div>
</div></div></div></div></div></div><div><div><div><div><div><div><p>JOB INFO</p>
<div><div><div><ul><div><div>Job Identification</div>
<div>25010490</div>
</div><div><div>Job Category</div>
<div>Information Technology</div>
</div><div><div>Posting Date</div>
<div>05/08/2026, 01:26 PM</div>
</div><div><div>Degree Level</div>
<div>Bachelor's Degree</div>
</div><div><div>Locations</div>
<div> <div></div><div><div>RFAB 300 W. Renner Road, Richardson, TX, 75080, US
</div></div></div></div><div><div>ECL/GTC Required</div>
<div>Yes</div></div></ul></div></div></div></div></div></div></div></div></div></div></div></div></div><p></p>

Agentic AI Engineer

Openkyber

<div><b>Job Title:</b> AI / ML Engineer<br>
<b>Location:</b> Dallas, TX or Memphis, TN Hybrid<br>
<b>Duration:</b> 6+ Months
<p>Project Role : AI / ML Engineer</p>
<p>Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution and developing AI applications using LLMs, RAG (Retrieval-Augmented Generation), and particularly agentic AI solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.</p>
<p>Must have skills :</p>
<ul><li>Advanced knowledge of Python specifically for machine learning and data science.</li>
<li>Experience with LLM frameworks such as LangChain, LlamaIndex, Semantic Kernel, or AutoGen.</li>
<li>Proficiency in cloud services related to ML/AI (e.g., Azure, OpenAI, Hugging Face, AWS, Google Cloud Platform).</li>
<li>Extensive experience in AI/ML development, particularly in NLP, and machine learning domains.</li>
<li>Hands-on experience in developing AI applications using LLMs, RAG (Retrieval-Augmented Generation), and particularly agentic AI solutions is essential</li>
<li>Proficiency in designing and maintaining AI/ML solutions that are cost-effective, accurate, and scalable.</li>
<li>Exceptional problem-solving skills and the ability to think analytically.</li>
<li>Strong communication and interpersonal skills, with the aptitude to navigate complex project requirements with clients and stakeholders.</li>
</ul><p>Nice to have: Certification as an Azure AI Engineer Associate or equivalent credentials is highly advantageous.</p>
<p>Experience with ML/DL frameworks like TensorFlow, Keras, PyTorch, and scikit-learn.</p>
<p>Experience with C# or Java, node.js.</p>
<p>With Regards, OpenKyber<br>
7525 Mitchell Road, Suite 106, Eden Prairie, MN 55344<br>
Email ID - hirings@openkyber.com</p>
<p><b>For applications and inquiries, contact:</b> hirings@openkyber.com</p></div>

OCI AI Services Engineer

DeepSource Technologies

<div><p>We are looking for a highly capable Senior AI Engineer / MLOps Engineer to join our team and lead the design, development, deployment, and optimization of scalable, production-grade AI and machine learning solutions. The ideal candidate will have strong hands-on experience across AI engineering, machine learning, MLOps, cloud-native architecture, and data engineering, with the ability to transform experimentation into reliable, business-ready systems.</p><p></p><p>
This role requires deep expertise in LLMs, RAG, agentic AI workflows, CI/CD automation, production ML lifecycle management, and modern data platforms. The selected candidate will be expected to lead end-to-end AI initiatives, work across multiple projects, collaborate with technical and business stakeholders, and ensure operational excellence across AI platforms.</p><p></p><p>
Key Responsibilities</p><ul><li>Design, develop, deploy, and maintain production-grade AI and machine learning systems end to end.</li><li>Build and optimize LLM-powered applications, including RAG pipelines, prompt workflows, agent-based systems, and multimodal AI use cases.</li><li>Develop intelligent workflows using tool-calling, orchestration frameworks, and contextual reasoning patterns.</li><li>Fine-tune, evaluate, and operationalize machine learning and foundation models for enterprise use cases.</li><li>Build and manage MLOps pipelines covering training, evaluation, model registration, deployment, monitoring, and retraining.</li><li>Implement CI/CD pipelines for ML and AI workflows to support automated testing, release management, and controlled deployments.</li><li>Establish model monitoring frameworks for drift detection, feature attribution, inference quality, and performance tracking.</li><li>Ensure reproducibility, reliability, and version control across AI/ML environments.</li><li>Architect scalable AI/ML platforms using modern compute, storage, orchestration, monitoring, and search services.</li><li>Build repeatable environments using Infrastructure as Code.</li><li>Support secure, high-availability, and cost-efficient deployment models across development, staging, and production environments.</li><li>Design scalable inference and serving patterns for variable workloads.</li><li>Build and maintain automated data pipelines, ETL/ELT workflows, and data processing frameworks for AI/ML consumption.</li><li>Ensure data quality, lineage, governance, and versioning to support dependable model training and inference.</li><li>Work with structured and unstructured datasets across data lakes, data warehouses, and operational systems.</li><li>Deliver analytics-ready datasets to downstream systems and applications.</li><li>Lead multiple AI initiatives in parallel, including planning, execution, and coordination with internal teams and stakeholders.</li><li>Work closely with product, engineering, data, and business teams to deliver production-ready AI capabilities.</li><li>Contribute to architecture decisions, technical documentation, best practices, and engineering standards.</li><li>Support knowledge sharing, technical leadership, and continuous improvement across the AI function.<br>
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<p></p><b>Requirements</b><ul><li><br>
Bachelor&rsquo;s degree in Computer Engineering, Computer Science, Artificial Intelligence, Data Science, or a related field.</li><li>5+ years of hands-on experience in AI engineering, machine learning engineering, MLOps, or data/ML platform engineering.</li><li>Proven experience deploying production AI/ML solutions in enterprise environments.</li><li>Strong programming experience in Python and SQL.</li><li>Strong experience with enterprise AI/ML architecture and delivery.</li></ul></div><p></p>

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