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>

Senior Ai Engineer - 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

MASTER-WORKS

<div>This is a highly skilled Machine Learning Engineer to design, build, deploy, and scale machine learning models that power data-driven products and intelligent systems. This role sits at the intersection of data science, software engineering, and MLOps, and requires strong hands-on experience turning models into production-ready solutions, programming experience in Python or R.
<ul><li>Design, develop, train, and optimize machine learning models for real applications or use cases.</li><li>
Translate business and product requirements into scalable ML/AI solutions.
</li><li>Implement feature engineering, model selection, tuning, and evaluation techniques.
</li><li>Develop , and deploy ML models into production environments with high availability and performance.</li><li>
Build and maintain ML pipelines (training, validation, deployment, monitoring).
</li><li>Monitor model performance, data drift, and model decay; retrain models as needed.
</li><li>Ensure models meet reliability, scalability, and security standards.
</li><li>Work closely with Data Scientists, Product Managers, and Software Engineers.
</li><li>Collaborate with data engineering teams to ensure high-quality, reliable data pipelines.</li><li>
Participate in design and code reviews, ensuring engineering best practices.
</li><li>Optimize models for latency, throughput, and cost.
</li><li>Implement experimentation frameworks (A/B testing, offline evaluation).
</li><li>Apply responsible AI principles, including fairness, explainability, and governance where required.</li></ul> 

Requirements 
<ul><li>
3&ndash;7+ years of hands-on experience in Machine Learning or applied AI roles.</li><li>
Strong programming skills in Python (and/or Java, Scala).
</li><li>Solid understanding of ML algorithms (supervised, unsupervised, deep learning).
</li><li>Experience with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
</li><li>Experience deploying models using Docker, Kubernetes, or cloud ML services.
</li><li>Strong knowledge of data structures, algorithms, and software engineering principles.
</li><li>Experience working in agile, cross-functional teams.</li><li>
Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services.
</li><li>Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).
</li><li>Experience with big data technologies (Spark, Kafka, Databricks).
</li><li>Background in NLP, Computer Vision, or Generative AI.
</li><li>Strong problem-solving and analytical thinking
</li><li>Production-first mindset
</li><li>Data-driven decision making
</li><li>High Collaboration and communication skills</li></ul></div>

AI Engineer

Master Works

<div>
 This is a highly skilled Machine Learning Engineer to design, build, deploy, and scale machine learning models that power data-driven products and intelligent systems. This role sits at the intersection of data science, software engineering, and MLOps, and requires strong hands-on experience turning models into production-ready solutions, programming experience in Python or R.
 
 
 <ul>
 <li>
 Design, develop, train, and optimize machine learning models for real applications or use cases
 </li>
 <li>
 Translate business and product requirements into scalable ML/AI solutions.
 </li>
 <li>
 Implement feature engineering, model selection, tuning, and evaluation techniques.
 </li>
 <li>
 Develop , and deploy ML models into production environments with high availability and performance
 </li>
 <li>
 Build and maintain ML pipelines (training, validation, deployment, monitoring).
 </li>
 <li>
 Monitor model performance, data drift, and model decay; retrain models as needed.
 </li>
 <li>
 Ensure models meet reliability, scalability, and security standards.
 </li>
 <li>
 Work closely with Data Scientists, Product Managers, and Software Engineers.
 </li>
 <li>
 Collaborate with data engineering teams to ensure high-quality, reliable data pipelines
 </li>
 <li>
 Participate in design and code reviews, ensuring engineering best practices.
 </li>
 <li>
 Optimize models for latency, throughput, and cost.
 </li>
 <li>
 Implement experimentation frameworks (A/B testing, offline evaluation).
 </li>
 <li>
 Apply responsible AI principles, including fairness, explainability, and governance where required
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 3-7+ years of hands-on experience in Machine Learning or applied AI roles
 </li>
 <li>
 Strong programming skills in Python (and/or Java, Scala).
 </li>
 <li>
 Solid understanding of ML algorithms (supervised, unsupervised, deep learning).
 </li>
 <li>
 Experience with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
 </li>
 <li>
 Experience deploying models using Docker, Kubernetes, or cloud ML services.
 </li>
 <li>
 Strong knowledge of data structures, algorithms, and software engineering principles.
 </li>
 <li>
 Experience working in agile, cross-functional teams
 </li>
 <li>
 Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services.
 </li>
 <li>
 Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).
 </li>
 <li>
 Experience with big data technologies (Spark, Kafka, Databricks).
 </li>
 <li>
 Background in NLP, Computer Vision, or Generative AI.
 </li>
 <li>
 Strong problem-solving and analytical thinking
 </li>
 <li>
 Production-first mindset
 </li>
 <li>
 Data-driven decision making
 </li>
 <li>
 High Collaboration and communication skills
 </li>
 </ul>
</div>

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

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