mlops engineer

DeepSource Technologies

<div>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.
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.
Key Responsibilities<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. 
</li></ul> 
 
Requirements<ul><li> 
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>

AI Architect - Riyadh,KSA

Eames Consulting

<div>
 
 
 AI/ML Engineer (Contract)
 
 
 
 
 Location:
 
 Florida (Required) -
 
 No Relocation
 
 
 
 
 Duration:
 
 6 Months (with possible extension)
 
 
 
 
 
 
 
 
 
 Overview
 
 
 
 We are seeking an experienced AI/ML Engineer to support the design, development, and deployment of scalable machine learning and generative AI solutions. This role will focus on building production-ready models, optimizing data pipelines, and collaborating with cross-functional teams to deliver high-impact AI initiatives.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, develop, and deploy machine learning models and AI solutions in production environments
 </li>
 <li>
 Build and optimize
 
 LLM-based applications
 
 (e.g., RAG pipelines, prompt engineering, agent workflows)
 </li>
 <li>
 Develop and maintain
 
 data pipelines
 
 to support model training, evaluation, and inference
 </li>
 <li>
 Implement
 
 MLOps best practices
 
 , including model versioning, monitoring, and automated retraining
 </li>
 <li>
 Collaborate with data engineers, product managers, and stakeholders to translate business requirements into technical solutions
 </li>
 <li>
 Evaluate model performance and continuously improve accuracy, scalability, and efficiency
 </li>
 <li>
 Ensure compliance with
 
 data governance, security, and responsible AI standards
 
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 6&ndash;7 years of experience in AI/ML engineering, data science, or related field
 </li>
 <li>
 Strong programming skills in
 
 Python
 
 (NumPy, Pandas, Scikit-learn)
 </li>
 <li>
 Hands-on experience with
 
 TensorFlow
 
 or
 
 PyTorch
 
 </li>
 <li>
 Experience building and deploying
 
 LLM-based solutions
 
 (RAG, embeddings, vector databases)
 </li>
 <li>
 Solid understanding of
 
 data engineering concepts
 
 (ETL, data pipelines, distributed processing)
 </li>
 <li>
 Experience with
 
 cloud platforms
 
 (AWS, Azure, or Google Cloud)
 </li>
 <li>
 Familiarity with
 
 MLOps tools
 
 (e.g., MLflow, Airflow, Docker, CI/CD pipelines)
 </li>
 <li>
 Strong problem-solving skills and ability to work independently in a fast-paced environment
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Experience with
 
 Databricks
 
 ,
 
 Snowflake
 
 , or similar data platforms
 </li>
 <li>
 Knowledge of
 
 vector databases
 
 (e.g., Pinecone, FAISS, Weaviate)
 </li>
 <li>
 Exposure to
 
 agentic AI frameworks
 
 (e.g., LangChain, LlamaIndex)
 </li>
 <li>
 Experience working in
 
 regulated environments
 
 (finance, healthcare, or government)
 </li>
 <li>
 Familiarity with
 
 AI governance frameworks
 
 (e.g., NIST AI RMF, Responsible AI practices)
 </li>
 </ul>
 
 
</div>

AI/ML Engineer

OpenArc, LLC.

<div>
 
 OpenArc - Empowering Your Career. As a leading IT staffing firm, we are dedicated to connecting talented professionals with your ideal opportunities. We are currently seeking a qualified AI Engineer to join our client&rsquo;s organization and contribute to their ongoing success.
 
 
 
 
 
 Job summary
 
 
 The AI Engineer will be responsible for designing, building, deploying, certifying, and maintaining production-grade generative AI and agentic business and technology solutions.
 
 
 Responsibilities:
 
 <ul>
 <li>
 Advance the organization&rsquo;s AI strategy with a strong emphasis on identifying high- value opportunities, defining technical roadmaps, prioritizing use cases, and advocating for responsible, extensible and scalable IA adoption.
 </li>
 <li>
 Collaborate with business and IT stakeholders to deeply understand current state processes and workflows in order to deliver AI powered solutions that deliver high-impact solutions driving measurable operational efficiency and transformation.
 </li>
 <li>
 Lead the full stack end-to-end development of custom AI solutions leveraging knowledge of MLOps, context management, and CICD practices to orchestrate AI agents and technology (e.g., Copilot AI, Snowflake AI, GitHub AI, AWS Bedrock, etc).
 </li>
 <li>
 Design, create, and implement reusable AI frameworks, prompt templates, reference architecture, and reference architectures to accelerate AI solution delivery across teams.
 </li>
 <li>
 Support the model evaluation, testing, and certification process: red-teaming, bias/fairness testing, accuracy benchmarking, hallucination detection, content safety filtering, and production readiness sign-off in regulated environments.
 </li>
 <li>
 Establish and enforce responsible AI governance practices, including aligning to the NIST AI Risk Management Framework.
 </li>
 <li>
 Collaborate with cloud, data and security architecture teams to build secure, extensible solutions
 </li>
 <li>
 Stay current with the latest capabilities in current and emerging AI agentic technology and frameworks.
 </li>
 <li>
 Experiment with alternative AI models and enhance the overall AI technology capabilities.
 </li>
 <li>
 Provide guidance on feasibility, risks and expected business impacts of AI initiatives.
 </li>
 <li>
 Draft clear documentation for AI models, data flows, AI solutions, APIs and operational procedures.
 </li>
 </ul>
 
 
 
 
 Requirements:
 
 <ul>
 <li>
 Experience in software engineering, data science, or related technical roles, with strong proficiency in coding, business and system design, and production deployment.
 </li>
 <li>
 Experience building and deploying generative AI solutions in enterprise environments
 </li>
 <li>
 Proficient in backend development using AI algorithms. Python, Java, Shell, Linux or Node.js, MCP, APIs, knowledge graphs, vector databases, &amp; data structures
 </li>
 <li>
 Demonstrated knowledge of MLOps, model lifecycle, and (CI/CD) practices.
 </li>
 <li>
 Designed and implemented full-stack AI solutions using modern MLOps and AI frameworks (e.g RAG) and platforms such as GitHub Agent, Snowflake agents, Copilot Studio and AWS Bedrock.
 </li>
 <li>
 Created reusable frameworks, prompt templates, and reference architectures to accelerate AI solution delivery across teams.
 </li>
 <li>
 Knowledge of Bank business applications is a plus
 </li>
 <li>
 Knowledge of data query, analysis, and scanning tools and techniques
 </li>
 </ul>
 
 
 
 
 
 
 
 At OpenArc, we prioritize your career success and strive to build exceptional technical teams for our clients. By understanding your experience and aspirations, we ensure to present you with rewarding and fulfilling opportunities.
 
 
 
 
 
 As an employee of OpenArc and our clients, you will be eligible to participate in a comprehensive benefits package.
 
 
 
 
 
 OpenArc is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.
 
</div>

Artificial Intelligence Engineer

SIDRAM TECHNOLOGIES

<div>
 
 Role: AI/ML Engineer - Python &amp; AWS
 
 
 
 
 Location- Reston, VA(In Person Interview at Herndon VA )
 
 
 
 
 Duration: Fulltime/Contract
 
 
 
 
 Onsite: 5 Days Onsite
 
 
 
 
 Job Description
 
 
 
 <ul>
 <li>
 Core Responsibilities (AI/ML, Python, AWS, GenAI)
 </li>
 <li>
 Design and implement end-to-end AI/ML and Generative AI solutions using Python, including model training, evaluation, optimization, and deployment.
 </li>
 <li>
 Build and maintain cloud native applications on AWS using services such as Lambda, ECS/Fargate, S3, API Gateway, DynamoDB, RDS/Aurora, SageMaker, and Bedrock.
 </li>
 <li>
 Develop high performance Python microservices (Fast API/Flask) enabling scalable data pipelines, model inference, and real time analytics.
 </li>
 <li>
 Architect and operationalize RAG pipelines, embeddings, vector databases, and LLM powered automation (chatbots, summarization, semantic search, anomaly detection).
 </li>
 <li>
 Implement CI/CD pipelines (GitHub/GitLab/CodePipeline) and infrastructure as code (Terraform/CloudFormation) for reliable, automated deployments.
 </li>
 <li>
 Build robust MLOps workflows, including model versioning, containerized training/inference, automated retraining, monitoring, and performance tuning.
 
 
 </li>
 </ul>
 
 Rachael
 
 
 
 
 IT Services | Development | Staffing
 
 
 
 
 URL: http:/www.sidramtech.com |
 
 
 
 
 Email: rachael@sidramtech.com
 
 
 
 
 Direct: 4705239688
 
 
 
 
 Led by 25+ Years of Industry Experience
 
</div>

AI/ML Engineer - Python &amp

Scotiabank

<div>Requisition ID: 257554 
 
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.<div> 
Purpose</div> 
<div></div>
<div>
The AI Engineer is an individual contributor responsible for designing, building, and operationalizing enterprise grade AI solutions in a highly regulated banking environment. This role will execute AI engineering and MLOps/LLMOps, ensuring AI solutions are secure, scalable, auditable, and production ready. You will work with Senior Engineers to build and deploy production grade AI systems end to end.</div> 
<div></div>
<div>
What You'll Do</div> 
<div></div>
<div>
Production AI Engineering (Build, Deploy, Run)</div>
<ul>
<li>Implement production‑grade AI services and pipelines (batch and real‑time) with strong focus on reliability, performance, and operational excellence in the cloud</li>
<li>Execute, manage and support the packaging and deployment of models and solutions as scalable services (APIs, jobs, agents) with clear SLAs, monitoring, alerting, and runbooks.</li>
<li>Own complex problem resolution across environments, including production incidents related to AI systems.</li>
</ul>
<div>Governance‑by‑Design (Banking &amp; Regulatory Alignment)</div>
<ul>
<li>Embed AI governance directly into engineering workflows, including:
<ul><li>Security and access controls</li>
<li>Data classification and handling</li>
<li>Model risk management requirements</li>
<li>Privacy and consent controls</li>
<li>Responsible AI principles</li>
<li>Auditability and regulatory traceability</li>
</ul></li><li>Partner closely with Risk, Compliance, Legal, and Architecture teams to ensure AI solutions meet internal and external regulatory expectations.</li>
</ul>
<div>Generative AI &amp; Advanced AI Capabilities</div>
<ul>
<li>Implementation of Generative AI patterns such as Retrieval‑Augmented Generation (RAG), embeddings, semantic search, and agent workflows.</li>
<li>Ensure GenAI solutions are grounded in approved data sources, governed access, logging, and retention policies.</li>
<li>Define evaluation and monitoring approaches for GenAI outputs in regulated use cases.</li>
</ul>
<div>Enterprise MLOps / LLMOps
</div><ul><li>Implement automated ML/LLM delivery pipelines covering training, evaluation, approval, deployment, and rollback.</li>
<li>Implement standards for model versioning, reproducibility, environment isolation, and controlled releases.</li>
<li>Reduce time‑to‑production while increasing safety, repeatability, and governance through automation.</li></ul> 
<div></div>
<div>
What You'll Bring</div> 
<div></div>
<ul>
<li>Bachelor&rsquo;s degree in Computer Science, Engineering, or equivalent practical experience.</li>
<li>3+ years of experience in cloud engineering, with 3+ years focused on AI/ML systems</li>
<li>Expert‑level proficiency in Python, SQL and cloud infrastructure</li>
<li>Hands‑on experience deploying AI solutions in cloud environments (Azure and GCP).</li>
<li>Deep understanding of production concerns: reliability, scalability, observability, cost, and security.</li>
<li>Experience delivering AI solutions in regulated industries (banking, financial services, insurance, healthcare).</li>
<li>Strong familiarity with model risk management, audit requirements, and regulatory review processes.</li>
<li>Hands‑on experience with enterprise MLOps / LLMOps tooling and platform design.</li>
<li>Experience designing platform‑level AI capabilities, not just individual models.</li></ul> 
<div></div>

Interested? 


If your experience is closely related but doesn&rsquo;t align perfectly with every qualification, we do encourage you to apply - you might be the right candidate for this or other roles at Scotiabank!

At Scotiabank, every employee is empowered to reach their fullest potential, respected for who they are and, embraced for their differences. That&rsquo;s why we work to grow and diversify talent and engage employees in a performance-oriented culture. 

What's in it for you? 


Scotiabank wants you to be able to bring your best self to work &ndash; and life, every day. With a focus on holistic well-being, our many flexible benefit programs are designed to help support your unique family, financial, physical, mental, and social health needs. 


#Dallas 


Location(s): United States : Texas : Dallas 
 
Scotiabank is a leading bank in the Americas. Guided by our purpose: &quot;for every future&quot;, we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.
 
 
At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.</div>

AI Engineer

NorthBay - Pakistan

<div>
 
 Role: Team Lead - Azure AI (Agentic) Engineer
 
 
 
 
 Location:
 
 Pakistan (hybrid work model)
 
 
 
 
 Client: Middle East (Government)
 
 
 
 
 
 About The Role
 
 
 
 NorthBay Solutions, an AWS global Consulting Partner with distributed teams across the US, Canada, UAE, India, and Pakistan, is hiring a high-caliber
 
 Azure AI Specialist (Team Lead)
 
 with deep expertise in building enterprise-grade
 
 Generative AI, RAG, and Agentic AI solutions
 
 on the Azure ecosystem.
 
 
 This role requires hands-on experience in designing scalable, multi-tenant AI systems, integrating LLMs, and building intelligent pipelines using Azure-native services.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design and deploy LLM-powered applications using Azure OpenAI for enterprise use cases
 </li>
 <li>
 Build and optimize Retrieval-Augmented Generation (RAG) pipelines using Azure AI Search (vector + hybrid search)
 </li>
 <li>
 Develop Agentic AI systems leveraging frameworks and tool-based reasoning approaches
 </li>
 <li>
 Implement custom Document Intelligence models for high-accuracy data extraction (e.g., IDs, structured documents)
 </li>
 <li>
 Architect multi-tenant AI deployments with scalability, security, and cost-efficiency in mind
 </li>
 <li>
 Develop and manage Knowledge Graphs for structured reasoning and contextual intelligence
 </li>
 <li>
 Apply advanced prompt engineering techniques (Few-shot, Chain-of-Thought, ReAct)
 </li>
 <li>
 Use Prompt Flow in Azure AI Studio for experimentation, testing, and versioning
 </li>
 <li>
 Design intelligent conversational systems with fallback handling and contextual memory
 </li>
 <li>
 Build and manage MLOps pipelines using Azure Machine Learning
 
 
 </li>
 </ul>
 
 Required Skills &amp; Experience
 
 
 
 <ul>
 <li>
 Overall 10+ years experience, with a focus on Azure OpenAI API (deployments, scaling, optimization)
 </li>
 <li>
 Proven expertise in building RAG pipelines using Azure AI Search
 </li>
 <li>
 Experience with vector databases and hybrid search architectures
 </li>
 <li>
 Practical experience in Agentic AI / multi-agent systems
 </li>
 <li>
 Hands-on with Azure AI Document Intelligence (Form Recognizer)
 </li>
 <li>
 Solid understanding of Knowledge Graphs and semantic modeling
 </li>
 <li>
 Expertise in prompt engineering &amp; LLM optimization techniques
 </li>
 <li>
 Experience with Prompt Flow (Azure AI Studio)
 </li>
 <li>
 Strong background in Python and cloud-native development
 </li>
 <li>
 Experience with Azure ML / MLOps pipelines
 </li>
 <li>
 Ability to design scalable and secure enterprise AI architectures
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience with LangChain, Semantic Kernel, or similar frameworks
 </li>
 <li>
 Exposure to multi-agent orchestration tools
 </li>
 <li>
 Prior experience working with enterprise clients or large-scale AI deployments
 </li>
 </ul>
</div>

Azure AI (Agentic) Specialist - Team Lead

Search 683+ Mlops engineer jobs near you this June. New roles added regularly across leading industries. Apply today.

683 mlops engineer jobs Near Me

AI Architect - Riyadh,KSA

AI/ML Engineer

AI Architect - Riyadh,KSA

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AI Engineer

Azure AI (Agentic) Specialist - Team Lead