ml platform engineer

Glow Beauty On Demand

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies

ML Platform Engineer

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies What We Offer * Opportunity to work on advanced ML and AI projects impacting millions of users in the Middle East * Competitive salary and benefits package * A collaborative, innovation-driven environment with cutting-edge tools and technologies * Career development in one of the fastest-growing tech ecosystems in the region

ML Platform Engineer Generative AI & Machine Learning

Johnson Controls

<div>Job Title: Senior Data Scientist &ndash; Data &amp; Analytics
Johnson Controls International (JCI) is seeking a Senior Data Scientist to join our innovative and impact-driven Data Science and Analytics team. This role is ideal for a seasoned expert with a deep understanding of machine learning, AI, and cloud data platforms, and a strong grasp of the latest advancements in Generative AI and Large Language Models (LLMs).
As a Senior Data Scientist, you will lead the development and deployment of scalable AI solutions&mdash;including those powered by LLMs&mdash;to accelerate digital transformation across our products, operations, and customer experiences. You'll play a critical role in shaping JCI&rsquo;s data science strategy, mentoring teams, and driving the use of AI to deliver measurable business value.
How you will do it
Advanced Analytics, LLMs &amp; Modeling<ul><li>
Design and implement advanced machine learning models including deep learning, time-series forecasting, recommendation engines, and LLM-based solutions (e.g., GPT, LLaMA, Claude).</li><li>
Develop use cases around enterprise search, document summarization, conversational AI, and automated knowledge retrieval using large language models.</li><li>
Fine-tune or prompt-engineer foundation models (e.g., OpenAI, Azure OpenAI, Hugging Face) for domain-specific applications.</li><li>
Evaluate and optimize LLM performance, latency, cost-effectiveness, and hallucination mitigation strategies for production use.</li></ul>
Data Strategy &amp; Engineering Collaboration<ul><li>
Work closely with data and ML engineering teams to integrate LLM-powered applications into scalable, secure, and reliable pipelines.</li><li>
Contribute to the development of retrieval-augmented generation (RAG) architectures using vector databases (e.g., FAISS, Azure Cognitive Search).</li><li>
Support the deployment of models using MLOps principles, ensuring robust monitoring and lifecycle management.</li></ul>
Business Impact &amp; AI Strategy<ul><li>
Partner with cross-functional stakeholders to identify opportunities for applying LLMs and generative AI to solve complex business challenges.</li><li>
Lead workshops or proofs-of-concept to demonstrate value of LLM use cases across business units.</li><li>
Translate complex model outputs, including those from LLMs, into clear insights and decision support tools for non-technical audiences.</li></ul>
Thought Leadership &amp; Mentorship<ul><li>
Act as an internal thought leader on AI and LLM innovation, keeping JCI at the forefront of industry advancements.</li><li>
Mentor and upskill data science team members in advanced AI techniques, including transformer models and generative AI frameworks.</li><li>
Contribute to strategic roadmaps for generative AI and model governance within the enterprise.</li></ul>
Qualifications &amp; Experience<ul><li>
Education in Data Science, Artificial Intelligence, Computer Science, or related quantitative discipline.</li><li>
5+ years of hands-on experience in data science, including at least 1&ndash;2 years working with LLMs or generative AI technologies.</li><li>
Demonstrated success in deploying machine learning and NLP solutions at scale.</li><li>
Proven experience with cloud AI platforms&mdash;especially Azure OpenAI, Azure ML, Hugging Face, or AWS Bedrock.</li></ul>
Technical Expertise<ul><li>
Proficiency in Python and SQL, including libraries like Transformers (Hugging Face), LangChain, PyTorch, and TensorFlow.</li><li>
Experience with prompt engineering, fine-tuning, and LLM orchestration tools.</li><li>
Familiarity with data storage, retrieval systems, and vector databases.</li><li>
Strong understanding of model evaluation techniques for generative AI, including factuality, relevance, and toxicity metrics.</li></ul>
Leadership &amp; Soft Skills<ul><li>
Strategic thinker with a strong ability to align AI initiatives to business goals.</li><li>
Excellent communication and storytelling skills, especially in articulating the value of LLMs and advanced analytics.</li><li>
Strong collaborator with a track record of influencing stakeholders across product, engineering, and executive teams.</li></ul>
Preferred Qualifications<ul><li>
Experience with IoT, edge analytics, or smart building systems.</li><li>
Familiarity with LLMOps, LangChain, Semantic Kernel, or similar orchestration frameworks.</li><li>
Knowledge of data privacy and governance considerations specific to LLM usage in enterprise environments.</li></ul></div>

AI/ML Platform Engineer

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies

ML Platform Engineer Generative AI & Machine Learning Infrastructure

Motive

<div>
 
 Who We Are
 
 
 
 Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks.
 
 
 Motive serves nearly 100,000 customers &ndash; from Fortune 500 enterprises to small businesses &ndash; across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector.
 
 
 Visit gomotive.com to learn more.
 
 
 
 About The Role
 
 
 
 As a Software Engineer on the
 
 ML Platform team
 
 , you will lead the effort to build systems that enable AI R&amp;D teams to deliver secure, highly scalable, distributed services. You will leverage technology such as Kubeflow, Kubernetes, Helm, Terraform, Python to build inference systems, infrastructure, and training pipelines as well as the distributed systems themselves. You will also provide guidance and mentorship to junior engineers.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Help define the direction for the team.
 </li>
 <li>
 Define and prioritize ML Platform initiatives.
 </li>
 <li>
 Enable teams to build features at scale by providing a foundation of reusable software components and infrastructure.
 </li>
 <li>
 Become one of the subject matter experts on the team. Create deployment pipelines; take code from git to production.
 </li>
 <li>
 Build infrastructure that enables fast, robust automated testing and validation.
 </li>
 <li>
 Improve the performance and reliability of existing systems.
 </li>
 <li>
 Coach junior engineers.
 
 
 </li>
 </ul>
 
 What We're Looking For
 
 
 
 <ul>
 <li>
 Building ML Ops infrastructure such as training pipelines.
 </li>
 <li>
 Building services to deliver inference in a scalable manner.
 </li>
 <li>
 Establishing monitoring best practices and implementing systems to enforce them.
 </li>
 <li>
 Practicing and advocating for best engineering practices throughout the ML org.
 </li>
 <li>
 B.S. or M.S. in Computer Science or a related field
 </li>
 <li>
 3+ years software development experience
 </li>
 <li>
 Experience improving the ML infrastructure with multiple stakeholders in a large organization.
 </li>
 <li>
 Experience in Python or similar language.
 </li>
 <li>
 Working knowledge of AWS services and technologies.
 </li>
 <li>
 Experience with Kubeflow pipeline development and management.
 </li>
 <li>
 Nice to have exposure with infrastructure as code and configuration management such as Terraform, CloudFormation.
 
 
 </li>
 </ul>
 
 Creating a diverse and inclusive workplace is one of Motive's core values. We are an equal opportunity employer and welcome people of different backgrounds, experiences, abilities and perspectives.
 
 
 
 
 Please review our Candidate Privacy Notice here .
 
 
 
 
 UK Candidate Privacy Notice here.
 
 
 
 
 The applicant must be authorized to receive and access those commodities and technologies controlled under U.S. Export Administration Regulations. It is Motive's policy to require that employees be authorized to receive access to Motive products and technology.
 
</div>

Software Engineer - ML Platform

Adlerqa Technologies pvt ltd.

Role: Lead Engineer (Python +ML OPS) Location: Chennai &amp; Bangalore Experience: 7+ Years Skills: Java, Python &amp; GoLang + MLOPs &amp; BigDataResponsibilities:<ul><li>Overall experience of 10+ years with proven track record of over-achieving engineering, platform delivery and scaling targets in high volume, innovative and fast-paced high-pressure&#8239;environment; proven results in delivery on platform products.</li><li>Solid proficiency in programming languages such as Python, Go and Java</li><li>Experience with cloud platforms (e.g., GCP, AWS, Azure) and containerization technologies (e.g., Docker, Kubernetes)</li><li>Experience with Vertex AI, Jupyter Notebook, Airflow, Kubeflow, Argo, GPU and HPC. Knowledge of GPU optimization and libraries is plus.</li><li>Experience building ML infrastructure or MLOps platforms and Bigdata platforms technologies such as Hadoop, BigQuery, Spark, Hive and HDFS.</li><li>Experience in machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models using various ML frameworks such as pytorch, tensorflow, scikit-learn, etc.</li><li>Experience in machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models using various ML frameworks such as pytorch, tensorflow, scikit-learn, etc.</li><li>Stay up-to-date with the latest advancements in AI/ML technology and industry trends and leverage this knowledge to enhance the platform's capabilities.</li><li>Strong communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner</li><li>Demonstrated leadership abilities, including the ability to inspire, mentor, and empower team members to achieve their full potential.</li></ul>Job Types: Full-time, PermanentPay: &#8377;697,440.81 - &#8377;2,038,186.93 per yearExperience:<ul><li>Python: 7 years (Preferred)</li><li>Java: 7 years (Preferred)</li><li>Big data: 7 years (Preferred)</li></ul>Work Location: In person

Lead Engineer

<div><div>Who we are:

Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks.

Motive serves nearly 100,000 customers &ndash; from Fortune 500 enterprises to small businesses &ndash; across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector.

Visit gomotive.com to learn more.</div><div><h3 class="jobSectionHeader">
About the Role:</h3>

As a Software Engineer on the ML Platform team, you will lead the effort to build systems that enable AI R&amp;D teams to deliver secure, highly scalable, distributed services. You will leverage technology such as Kubeflow, Kubernetes, Helm, Terraform, Python to build inference systems, infrastructure, and training pipelines as well as the distributed systems themselves. You will also provide guidance and mentorship to junior engineers.
<h3 class="jobSectionHeader">
What You'll Do:</h3>
<ul><li>Help define the direction for the team.</li>
<li>Define and prioritize ML Platform initiatives.</li>
<li>Enable teams to build features at scale by providing a foundation of reusable software components and infrastructure.</li>
<li>Become one of the subject matter experts on the team. Create deployment pipelines; take code from git to production.</li>
<li>Build infrastructure that enables fast, robust automated testing and validation.</li>
<li>Improve the performance and reliability of existing systems.</li>
<li>Coach junior engineers.</li>
</ul><h3 class="jobSectionHeader">What We're Looking For:</h3>
<ul><li>Building ML Ops infrastructure such as training pipelines.</li>
<li>Building services to deliver inference in a scalable manner.</li>
<li>Establishing monitoring best practices and implementing systems to enforce them.</li>
<li>Practicing and advocating for best engineering practices throughout the ML org.</li>
<li>B.S. or M.S. in Computer Science or a related field</li>
<li>3+ years software development experience</li>
<li>Experience improving the ML infrastructure with multiple stakeholders in a large organization.</li>
<li>Experience in Python or similar language.</li>
<li>Working knowledge of AWS services and technologies.</li>
<li>Experience with Kubeflow pipeline development and management.</li>
<li>Nice to have exposure with infrastructure as code and configuration management such as Terraform, CloudFormation.</li></ul></div><div> 
Creating a diverse and inclusive workplace is one of Motive's core values. We are an equal opportunity employer and welcome people of different backgrounds, experiences, abilities and perspectives. 

The applicant must be authorized to receive and access those commodities and technologies controlled under U.S. Export Administration Regulations. It is Motive's policy to require that employees be authorized to receive access to Motive products and technology.

#LI-Remote</div></div>

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