generative ai engineer

Openkyber

<div>We are looking for FullStack AI Engineer for our client in Malvern, PA Job Title: FullStack AI Engineer Job Location: Malvern, PA Job Type: Contract Job Description: Pay Range: $65hr - $70hr Solution Design Implementation Design and implement endtoend generative AI solutions leveraging services like Amazon Bedrock including Agents Knowledge Bases and Guardrails. Model Development Optimization Finetune and customize large language models LLMs and other generative models GANs VAEs for specific business needs ensuring optimal performance and scalability. Prompt Engineering RAG Apply prompt engineering methodologies and build RetrievalAugmented Generation RAG systems to enhance model accuracy reliability and contextual understanding. Build CICD pipelines to automate the model lifecycle including training deployment monitoring and retraining. Cloud Infrastructure IaC Develop and manage robust cloud infrastructure using Infrastructure as Code IaC tools like AWS CloudFormation AWS CDK or Terraform. Collaboration Documentation Work with product managers to integrate AI capabilities into existing systems and create technical documentation best practices and tutorials. Security Compliance Ensure all AI solutions meet AWS best practices for security compliance scalability and cost optimization. Proficiency in Python is essential along with experience in languages like Java or TypeScript. Handson experience with core AWS services including S3 Lambda EC2 DynamoDB API Gateway Step Functions Glue and Athena Strong understanding and experienc in orchestration frameworks like LangChain. Technical Concepts Expertise in Generative AI architectures LLMs vector databases statistical methods and data processing. Strong problemsolving analytical and communication skills for working in crossfunctional teams and interacting with customers.
For applications and inquiries, contact: hirings@openkyber.com</div>

OCI AI Infrastructure Engineer

MISO

<div>Help shape the future of energy through AI-driven insights!

At MISO, our Analytics and Forensics team is redefining how data powers the energy markets. We build and maintain advanced analytical assets that detect, investigate, and ultimately help prevent market risk events, strengthening reliability for 45 million people. This is more than an AI role. It&rsquo;s an opportunity to shape the future of energy markets. Your work will directly impact how risks are detected, analyzed, and prevented, helping ensure a reliable and resilient power grid.

We&rsquo;re looking for a Principal AI Engineer who is passionate about pushing boundaries with machine learning, generative AI, and large language models. In this role, you&rsquo;ll design and scale cutting-edge AI solutions that unlock deeper insights into market behavior and drive innovation across the energy sector. You won&rsquo;t just build models, you&rsquo;ll build mission-critical intelligence that powers one of the most important infrastructures in the world.

Your responsibilities as our Principal AI Engineer will include:
<ul>
<li>Designing, building, and deploying AI-driven solutions, including ML models, generative AI applications, and intelligent agents.</li>
<li>Developing and operationalizing LLM-powered solutions (RAG, prompt engineering, agent workflows) to extract insights from structured and unstructured data.</li>
<li>Building scalable infrastructure and platforms to train and serve models at enterprise scale.</li>
<li>Prototyping and delivering minimal viable products (MVP), proofs of concept, and production-ready AI solutions.</li>
<li>Partnering with data scientists, engineers, and technology teams to integrate AI into real-time and batch pipelines.</li>
<li>Evaluating and recommending emerging tools, frameworks, and APIs (e.g., OpenAI, Hugging Face, Vertex AI).</li>
<li>Applying AI to anomaly detection and market behavior analysis across electrical markets</li>
<li>Driving insights from unstructured sources.</li>
<li>Contributing to innovation through experimentation with foundation models, vector databases, and optimization techniques.</li>
</ul>
Experience needed for our Principal AI Engineer include:
<ul>
<li>A Bachelor&rsquo;s degree in Computer Science, Software Engineering, Data Science, Data Analytics or related field. Master&rsquo;s degree preferred.</li>
<li>3+ years of real-world experience building AI.</li>
<li>10-12 years of experience in building machine learning solutions in a professional environment.</li>
<li>Demonstrated experience across multiple disciplines such as:
<ul><li>Predictive modeling</li>
<li>Natural language processing</li>
<li>Data pipelines and automation</li>
<li>API development and integration</li>
<li>Data visualization and segmentation</li>
<li>Applied mathematical modeling</li>
</ul></li><li>Proven ability to take ideas from concept to scalable production solutions.</li>
<li>Hands-on experience with generative AI and large language models (fine-tuning, RAG, prompt engineering, agent frameworks).</li>
</ul>
Some of the technical proficiencies needed for our Principal AI Engineer include:
<ul>
<li>Apache Spark, Databricks, or Synapse</li>
<li>Azure Data Factory &amp; Azure Machine Learning Studio</li>
<li>MLflow and model lifecycle management</li>
<li>OpenAI and/or Hugging Face ecosystems</li>
<li>SQL and database querying</li>
<li>Docker and containerized deployments</li>
<li>R and Python (required)</li>
</ul>
Appropriate level will be determined based upon experience and knowledge. 
 
Transformative innovation is happening in the electric industry, from digitalizing homes and distributed resources to renewable energy and an ever-changing grid. MISO manages the electricity superhighway in the Central U.S. and through use of groundbreaking research and advanced technology, our highly skilled employees ensure power flows reliably to 45 million Americans. Operating the electricity grid, running a robust energy market, planning for a bright future &ndash; it&rsquo;s what our immensely hardworking and dedicated team does every day.
 
 
The base salary compensation range being offered for this role is $168,000 - $193,000 USD annually. Base salary range for this position is included in accordance with requirements of various state/local pay transparency legislation. Please note that salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, and qualifications/experience.
 
 
Position is also eligible for an annual bonus if individual performance and company objectives are met. At MISO we offer a comprehensive benefits package, including 401k, vacation, sick and safe time, available on your first day of employment.

#DiscoverMISO #MISOCareers #lifeatMISO #weareMISO

MISO, What We Do

#LI-ONSITE 
#LI-JH1</div>

Principal AI Engineer

Microsoft

<div>Overview<div> 
As an AI Engineer in the Office AI team, you work to enhance Office productivity with AI-driven experiences and services across key applications. The team builds the core platforms and experiences that bring large language models (LLMs) and realtime intelligence into Office apps. These platforms are key components of Microsoft Copilot, combining the power of large language models with enterprise data and native integration with Office apps to streamline productivity, including content generation, navigation, comprehension and more.
We are looking for a creative AI Engineer who will collaborate with software engineers, researchers, and product managers to express product needs as well defined machine learning problems, push the state of the art in LLMs and bring prototypes all the way to planet scale production. You&rsquo;ll build the engineering that makes AI work in production: you will build APIs, platforms and services around AI features; design data pipelines and feedback loops; deploy and finetune state of the art deep learning models; orchestrate prompts and tools; and monitor AI specific signals&mdash;such as drift, hallucinations, safety and cost&mdash;alongside traditional service reliability metrics.
Join us to empower people through AI, bringing cutting edge deep learning into everyday work at scale. At Microsoft, our mission is to empower every person and every organization to achieve more; we show up with a growth mindset, innovate to empower others, and collaborate to realize shared goals. Rooted in respect, integrity, and accountability, we foster an inclusive culture where everyone can thrive. If you are passionate about applying state of the art AI to positively impact millions, this role is for you.
Microsoft&rsquo;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</div> 
Responsibilities 
<div><ul><li>
Ship features with PM &amp; Engineering. Co own scenario goals; translate product requirements into scientific plans and productionized solutions that meet quality/latency/cost targets.</li><li>
Generative AI and advanced technologies. Apply knowledge of generative AI, large language models, and modern frameworks to develop intelligent features and automation within the service.</li><li>
Azure platform integration. Deploy, integrate, and manage AI powered solutions within the Azure ecosystem, ensuring security, scalability, and compliance with best practices.</li><li>
Continuous learning and mentoring. Stay current with advances in generative AI and software engineering. Invest time in learning new tools and frameworks, propose improvements to build processes, and share knowledge with colleagues.</li></ul></div> 

Qualifications 
Required Qualifications:<ul><li>
Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python<ul><li>
OR equivalent experience.</li></ul></li></ul>
Preferred Qualifications:<div><ul><li>
Master&rsquo;s degree in computer science or related field.</li><li>
1 + years of experience designing and running infrastructure systems that operate globally on a large scale.</li><li>
Experience deploying AI models into production environments and building systems that monitor and retrain models automatically.</li><li>
Passion for mentoring others and contributing to an inclusive team culture.</li><li><div>
Distributed systems and cloud. Familiarity with Azure services, microservices architectures, and distributed storage systems (experience with Cosmos DB or similar is a plus). Ability to design and run fault tolerant infrastructure on a large scale and to implement secure, compliant solutions.</div></li><li><div>
AI and machine learning skills. Handson experience with generative AI or machine learning frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and a solid understanding of LLM concepts, embeddings, and prompt engineering.</div></li></ul></div> 
 
 
Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $131,400 - $215,400 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: 
https://careers.microsoft.com/us/en/us-corporate-pay 
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. 
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process.</div>

AI Engineer II

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

Apple

The Intelligence Platform team empowers clients across Apple&rsquo;s operating systems with a high quality user-centric search and data platform, and the primary inference platform that enable next generation user experiences for Apple Intelligence. We are in search of an accomplished and driven Machine Learning Engineer who has a robust understanding of Large Language Models, Generative AI and high-performance systems computing. Your primary role will involve working with our cross-functional teams that build foundation models, as well as our client teams that want to run inference using these models and continue the development of our inference stack. By contributing to our team, you&rsquo;ll play an integral part in developing Siri, Photos, Music, and various other services, leaving a significant footprint on the evolution of our AI platforms. Join us in our exciting journey as we push the frontiers of Machine Learning and Generative AI. Your expertise and contributions will be invaluable in shaping the future of our Intelligence Platform. 
 
Description 
 
As a Machine Learning Engineer on the Apple Intelligence Platform Inference Tean, you&rsquo;ll join a phenomenal team of top-performing engineers and and will be entrusted with a range of responsibilities. Your tasks will include: 
 
Leading the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields. 
 
Translating the latest research into high-performing systems and a model serving stack that can be practically applied to enhance user experiences. 
 
Contribute to setting the team&rsquo;s strategic direction, cultivating an environment that encourages innovation and professional growth. 
 
Collaborating with various teams to develop and implement evolving requirements of our clients on the GenAI inference stack, ensuring performance optimization and alignment with broader business goals. 
 
Preferred Qualifications 
 
An advanced degree (Master&rsquo;s or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a related field is required 
 
Ongoing professional development in Machine Learning and Artificial Intelligence domains is expected. 
 
Minimum Qualifications 
 
In-depth experience in Machine Learning, with a particular emphasis on Large Language Models (LLMs) and Generative AI. 
 
Published research in the field of Machine Learning or AI is highly desirable, indicating an ability to not only understand but also contribute to cutting-edge research. 
 
Proven ability to comprehend, interpret, and apply cutting-edge research into tangible applications. 
 
Proven problem-solving and leadership abilities, with the capacity to steer the team&rsquo;s research and practical applications in a collaborative and fast-paced environment. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Machine Learning Engineer - Large Language Models & Generative AI Inference

Blue Matter

<div>Blue Matter is a rapidly growing management consultancy focused on the biopharmaceutical industry. We partner with clients to help them achieve commercial success across the lifecycle of their products, portfolios, and organizations.
Blue Matter is hiring for the Technology and Operations Practice within the Blue Matter Insights Team. Our Technology &amp; Operations practice integrates strategy, data, and AI to deliver scalable, technology-enabled solutions for BioPharma Clients. The practice has developed a category-defining platform called Twine&trade;&mdash; an AI-first customer intelligence platform purpose-built for life sciences that is already seeing strong traction in the market. The successful candidate will play a direct role in shaping, enhancing, and scaling Twine as a core capability within our portfolio.
As an AI Engineer / Senior AI Engineer, you will work across Blue Matter as a technical expert in AI and emerging technologies, playing a key role in designing, building, and deploying AI-powered solutions for both internal teams and clients. You will be at the forefront of integrating APIs, building proof-of-concepts (POCs), developing internal applications, and creating client-facing tools and services. This role is ideal for someone who is passionate about staying current with the rapidly evolving AI landscape and eager to apply cutting-edge techniques to solve real-world problems in life sciences.
Primary Responsibilities
As a key member of cross-functional client-facing teams, develop and execute project plans to support initiatives that include, but are not limited to:<ul><li>
Design, develop, and deploy AI/ML solutions and Generative AI applications to support commercial data and analytics for life sciences companies</li><li>
Integrate third-party AI APIs (e.g., OpenAI, Anthropic, Google Gemini, Hugging Face) into internal and client-facing applications to deliver intelligent, scalable solutions</li><li>
Build proof-of-concepts (POCs) and rapid prototypes to demonstrate the value of AI-driven approaches for product launch analytics, drug discovery, patient analytics, and data operations</li><li>
Develop and maintain internal tools and applications that streamline workflows, automate operational processes, and enhance team productivity using AI</li><li>
Build client-facing tools and services that leverage AI to deliver actionable insights, interactive dashboards, and intelligent recommendations</li><li>
Utilize cloud-service providers (e.g., AWS, Azure, or GCP) including services such as S3, EC2, Lambda, Azure OpenAI, and SageMaker to build and deploy scalable AI solutions</li><li>
Collaborate with onshore/offshore teams to ensure timely, high-quality deliverables, providing technical guidance and code reviews</li><li>
Design and implement data pipelines and ETL processes to support AI model training, fine-tuning, and inference workflows</li><li>
Investigate and evaluate emerging AI frameworks, tools, and models to continuously improve the team&rsquo;s AI capabilities and stay ahead of industry developments</li><li>
Contribute to Blue Matter&rsquo;s Internal platform rollout and other AI-powered product initiatives in client environments</li><li>
Address client questions, gather requirements, and deliver AI-powered solutions aligned with business goals</li><li>
Ensure project success through effective collaboration and meeting deadlines using agile delivery model</li><li>
Stay current with the latest advancements in AI/ML, LLMs, prompt engineering, RAG, agents, and related technologies, and evangelize best practices across the organization</li></ul>
Desired Experience and Skills<ul><li>
Hands-on experience building AI/ML applications, including working with LLMs, Generative AI, and NLP frameworks</li><li>
Strong proficiency in Python and experience with AI/ML libraries and frameworks (e.g., LangChain, LlamaIndex, Hugging Face Transformers, PyTorch, TensorFlow)</li><li>
Proven experience integrating AI APIs (e.g., OpenAI, Anthropic, Google Vertex AI, Azure OpenAI) into production-grade applications</li><li>
Experience building and deploying internal tools and applications (e.g., using Streamlit, Gradio, Flask, FastAPI, or React)</li><li>
Ability to build client-facing tools and services that are reliable, user-friendly, and production-ready</li><li>
Expertise in building proof-of-concepts (POCs) and rapid prototypes to validate AI-driven solutions</li><li>
Experienced with cloud platforms (AWS, Azure, GCP) and services</li><li>
Proficient in API development (RESTful/GraphQL) and version control (e.g., Git)</li><li>
Expertise in SQL, Python, and databases</li><li>
Familiar with data pipeline tools (e.g., Airflow, dbt) and data warehouse technologies (e.g., Snowflake, Redshift, Databricks)</li><li>
Knowledge of prompt engineering, RAG (Retrieval-Augmented Generation), fine-tuning, and AI agent frameworks</li><li>
Strong knowledge of AI safety, responsible AI practices, and model evaluation techniques</li><li>
Knowledge of US pharma datasets and healthcare concepts is a plus</li><li>
Strong problem-solving, communication, and client-facing skills</li><li>
Proficient in Agile/Scrum and project management tools (e.g., JIRA, Smartsheet)</li><li>
Genuine passion and curiosity for ongoing AI development, with a demonstrated habit of learning and experimenting with new AI tools, models, and techniques</li><li>
Excellent communication and presentation skills (internal and client facing)</li></ul>
Preferred Qualifications<ul><li>
Advanced degree(s) (PhD, MD, MBA, or MS) in Computer Science, AI/ML, Data Science, or a related field</li><li>
4+ years of AI/ML engineering experience (AI Engineer) or 6+ years (Senior AI Engineer), including client-facing roles experience</li><li>
Demonstrated ability to integrate business and industry knowledge in developing creative AI solutions</li><li>
Active contributions to open-source AI projects, personal AI projects, or published research in AI/ML</li><li>
Passion for Generative AI and its applications in life sciences and healthcare</li></ul>
Compensation:
Base salary range: $100,000 - $150,000 per year. Generous incentive compensation structure. 
 
Benefits Package:<ul><li>
401k - generous employer match with immediate vesting and financial planning resources</li><li>
Comprehensive medical, dental and vision coverage options effective day 1 of employment</li><li>
Flexible spending account (FSA) or Health Savings Account (HSA)</li><li>
Company paid insurances including Short- and Long-Term Disability and Life insurance as well as additional voluntary options</li><li>
Paid parental leave for all new parents</li><li>
Health &amp; Wellness Benefit (e.g., gym memberships; $1000 reimbursement annually)</li><li>
Employee Assistance Program</li><li>
Generous paid time off including vacation, sick days, floating and company holidays</li></ul><div>
Blue Matter is an equal opportunity employer and does not discriminate against otherwise qualified applicants on the basis of race, color, religion, ancestry, age (40 and over), sex (including gender identity, sexual orientation and pregnancy), national origin, disability, marital status, parental status, genetic information, political affiliation, protected veteran status, or any other characteristic protected by law.</div>
YFln9UxC3u</div>

AI Engineer / Senior AI Engineer

<div>Title: AI/ML Engineer Number of Openings: 2 Location: Malvern, PA (3 days on-site required) 
Interview Process
Systems Technical Screening (1 hour MS Teams Video) 1 hour MS Teams Video I/V with client team
Core Responsibilities
<ul><li>Agentic AI &amp; MCP Integration: Implement agentic frameworks (e.g., LangGraph, AutoGen) and Model Context Protocol (MCP) for secure tool orchestration.</li>
<li>Generative AI Development: Build LLM-based applications with RAG, structured output, and evaluation frameworks.</li>
<li>Agentic Cloud Deployment &amp; Integration: Design and deploy agentic AI services in cloud environments, integrating models, tools, APIs, and data sources to deliver scalable, autonomous workflows.</li>
<li>Databricks &amp; Lakehouse Engineering: Develop and optimize ML and GenAI workloads using Databricks, including Sparkbased data pipelines, feature engineering, and model training/inference on the Lakehouse platform.</li>
<li>Unity Catalog &amp; Governance: Implement Unity Catalog for centralized data, model, and feature governance, ensuring secure access control, lineage tracking, and compliance across ML and GenAI assets.</li>
<li>AWS ML Engineering: Deploy models using SageMaker pipelines, ECS/ECR, Lambda; manage CI/CD and monitoring.</li>
<li>Security &amp; Identity: Integrate Okta/JWT token for API and service authentication; enforce token validation and claims.</li>
<li>Governance : Deliver artifacts required by MDLC/MPLC (Model Documents, Data Dictionary, Monitoring Plan).</li>
<li>Collaboration: Partner with PO, and business stakeholders to align solutions with objectives.</li>
</ul>Responsibilities
<ul><li>Design, develop, and optimize complex data pipelines using machine learning engineering best practices to ensure scalability, efficiency, and reliability.</li>
<li>Develop and implement robust MLOps pipeline to support the deployment, monitoring, and lifecycle management of AI/ML models in production environments.</li>
<li>Integrate and maintain data and model pipelines, proactively diagnosing data quality issues and documenting assumptions.</li>
<li>Collaborate closely with data scientists to validate model-ready datasets and ensure thorough, accurate feature documentation.</li>
<li>Conduct exploratory data analysis and discovery on raw data sources, incorporating business context to support model development.</li>
<li>Track data lineage and perform root cause analysis during early-stage exploration or issue resolution.</li>
<li>Partner with internal stakeholders to understand business processes and translate them into scalable analytical solutions.</li>
<li>Develop and maintain model monitoring scripts, investigate alerts, and coordinate timely resolutions.</li>
<li>Act as a subject matter expert in machine learning engineering on cross-functional teams, contributing to high-impact initiatives.</li>
<li>Stay current with advancements in AI/ML and evaluate their applicability to business challenges.</li>
</ul>Qualifications
<ul><li>Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred).</li>
<li>6+ years of experience across Artificial Intelligence (AI) / Machine Learning (ML) engineering, data engineering, and MLOps implementation, including: Designing and deploying production-grade ML systems.</li>
<li>Building scalable data pipelines and ML workflows.</li>
<li>Managing model lifecycle in cloud environments.</li>
<li>Proficient in Python and familiar with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.</li>
<li>Handson experience with Databricks, including: Sparkbased data processing and feature engineering Databricks ML/MLflow for experiment tracking and model management Integrating Databricks with cloudnative ML services</li>
<li>Experience implementing Unity Catalog for centralized governance of data, features, and models, including access controls, lineage, and auditability.</li>
<li>Strong understanding and experience in AWS Machine Learning Stack including: AWS SageMaker AWS Glue AWS Bedrock AWS Data Pipelines AWS Lambda Functions</li>
<li>Experience with Generative AI model development builing LLM based applications with RAG.</li>
<li>Experience implementing agentic frameworks (e.g., LangGraph, AutoGen) and Model Context Protocol (MCP) for orchestration.</li>
<li>Knowledge of React UI, GraphDB, and GenAI model performance evaluation</li>
<li>Experience with CI/CD, containerization (e.g., Docker), and orchestration tools (e.g., Kubernetes).</li>
<li>Solid grasp of software engineering principles including testing, version control (e.g., Git), and security.</li>
<li>Familiarity with the Machine Learning Development Lifecycle (MDLC) and best practices for reproducibility and scalability.</li>
<li>Strong communication and collaboration skills, with experience working across technical and business teams.</li>
<li>Ability to anticipate ambiguity and devise scalable solutions to address it.</li>
</ul>Nice to Have
<ul><li>Knowledge of data governance, model explainability, and responsible AI practices.</li>
</ul>For applications and inquiries, contact: hirings@openkyber.com</div>

Okta

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