machine learning architect

Openkyber

<div>Hi, This is OpenKyber from OpenKyber. We have an opportunity with one of our direct clients, and I'd like to share the details with you. Please review the information below and let me know if you're interested. Kindly share your updated resume if you'd like to be considered.
Job Title: Generative AI Architect Location: Montvale, NJ (Hybrid onsite)
Job Overview: We are seeking an AI Architect specializing in Generative AI and Large Language Models (LLMs) to help design, deploy, and scale AI solutions for enterprise clients. This role requires deep expertise in machine learning and data science , particularly in the design, evaluation, and operationalization of modern language models and generative AI systems . The AI Architect will work closely with engineering teams and client stakeholders to translate cutting-edge AI capabilities into reliable production systems , while ensuring governance, transparency, and responsible AI practices . The ideal candidate combines technical depth, research awareness, and strong communication skills , enabling them to represent our company confidently in front of senior client stakeholders. This is a full-time, in-office role , with some days at client and direct engagement with enterprise teams.
Required Qualifications Master's degree in Data Science, Machine Learning, Computer Science, or related field . Strong expertise in machine learning fundamentals and modern generative AI technologies . Proven experience designing and deploying AI/ML systems in production environments . Deep knowledge of: Large Language Models Generative AI architectures ML pipelines and model lifecycle management Experience working with AI frameworks and ecosystems used for building GenAI applications . Experience implementing AI governance, explainability, and responsible AI practices . Strong understanding of enterprise software architecture and distributed systems .
Preferred Qualifications Experience with agentic AI systems and orchestration frameworks . Experience building RAG-based AI systems . Familiarity with AI platform engineering and scalable AI infrastructure . Contributions to AI research, open-source projects, or technical publications . Experience working with enterprise clients in regulated industries .
Key Skills Technical Skills Machine Learning &amp; Data Science Large Language Models (LLMs) Generative AI systems AI agents and agentic architectures MLOps and model lifecycle management AI governance and explainability Professional Skills Strong analytical and problem-solving capabilities Excellent communication and presentation skills Ability to simplify complex AI concepts for diverse audiences Collaborative mindset and ability to work effectively within teams Client-facing professionalism and credibility Work Environment Full-time in-office role with collaboration across engineering and client teams. Weekly client visits for workshops, architecture discussions, and solution design sessions . High collaboration with data scientists, engineers, architects, and business stakeholders .
What Success Looks Like in This Role Successfully architect and deliver production-grade AI systems . Become a trusted AI advisor to both internal teams and client stakeholders. Ensure responsible and governed adoption of AI technologies . Help organizations translate GenAI innovation into real operational value .
Educational Qualifications: Required - Bachelor's degree in Computer Science, Information Technology, Computer Engineering or closely related or equivalent. Preferred - Master's degree in Management Information Systems (MIS), Computer Science, Big Data or Analytics or equivalent.
Travel: Open to travel based-up on the nature of the engagement.
Thanks &amp; Regards OpenKyber Resource Manager (w): (E): 2260 Haggerty Road, Suite 285 Northville, MI 48167
Equal Employment Opportunity OpenKyber employment does not discriminate on the basis of race, religion, gender, sexual orientation, age or any other basis as covered by federal, state, or local law. Employment decisions are based solely on qualifications, merit and business needs.
For applications and inquiries, contact: hirings@openkyber.com</div>

Generative AI Intern

Valleysoft

<div>Valleysoft | Center of Excellence is a regional IT services provider based in Egypt, serving clients globally since 2006. The company collaborates with global partners like Oracle to address diverse business and technical challenges, from enterprise application development to process management. Valleysoft's vendor-neutral and process-oriented approach, coupled with operational maturity, ensures high-quality and cost-effective services for clients.
Job Summary
We are seeking a highly experienced Lead MLOps Architect with deep AWS expertise to lead the design, architecture, and governance of enterprise-grade ML platforms. This role requires strong leadership capabilities, hands-on expertise in scalable ML systems, and experience managing large production environments.
Key Responsibilities<ul><li>
Architect and lead enterprise-scale MLOps platforms on AWS.</li><li>
Define best practices for ML lifecycle management, deployment standards, and governance.</li><li>
Lead production deployment of ML models using AWS-native services.</li><li>
Design automated CI/CD pipelines for ML workflows and infrastructure.</li><li>
Implement advanced monitoring, drift detection, retraining automation, and observability.</li><li>
Ensure high availability, scalability, security, and cost optimization.</li><li>
Establish model versioning, reproducibility, and experiment tracking standards.</li><li>
Lead troubleshooting of complex production issues.</li><li>
Mentor and lead a team of MLOps and platform engineers.</li><li>
Collaborate with stakeholders to align ML platform strategy with business objectives.</li></ul> 

Requirements 

Required Skills &amp; QualificationsMLOps &amp; Machine Learning<ul><li>
10&ndash;12 years of overall experience with strong focus on ML production systems</li><li>
Proven experience leading ML platform architecture and large-scale deployments</li><li>
Deep understanding of ML lifecycle management, governance, and reproducibility</li><li>
Hands-on experience with TensorFlow, PyTorch, Scikit-learn</li><li>
Strong experience with MLflow or enterprise model management tools</li></ul>
AWS Cloud (Mandatory)<ul><li>
Advanced hands-on expertise in:</li><li><ul><li>
Amazon SageMaker (training, pipelines, endpoints)</li><li>
S3, EC2, Lambda</li><li>
ECR, ECS, EKS</li><li>
IAM, CloudWatch</li></ul></li><li>
Experience designing secure, compliant, and scalable ML architectures</li><li>
Experience implementing cost optimization strategies on AWS</li></ul>
DevOps, Containers &amp; IaC<ul><li>
Strong expertise in Docker and Kubernetes (EKS)</li><li>
Advanced CI/CD implementation</li><li>
Infrastructure as Code using Terraform and/or CloudFormation</li><li>
Experience implementing GitOps practices</li></ul>
Programming &amp; Data<ul><li>
Expert-level Python skills</li><li>
Experience designing robust data pipelines</li><li>
Strong understanding of SQL/NoSQL systems</li><li>
Exposure to streaming or real-time ML systems</li></ul>
Preferred Qualifications<ul><li>
AWS Professional-level certifications</li><li>
Experience with ML security, explainability, and regulatory compliance</li><li>
Experience building enterprise feature stores</li><li>
Exposure to real-time inference systems</li></ul></div>

Lead MLOps Architect - AWS

Credera

<div><div>Credera is a global consulting firm that combines transformational consulting capabilities, deep industry knowledge, AI and technology expertise to deliver valuable customer experiences and accelerated growth across various industries. We continuously evolve our services to meet the needs of future organizations and reflect modern best practices. Our unique global approach provides tailored solutions, transforming the most influential brands and organizations worldwide.

Our employees, the lifeblood of our company, are passionate about making an extraordinary impact on our clients, colleagues, and communities. This passion drives how we spend our time, resources, and talents. Our commitment to our people and work has been recognized globally. Please visit our employer awards page: https://www.credera.com/awards-and-recognition.</div>
As a Senior Architect in Credera's Data capability group, you will lead teams in implementing modern data architecture, data engineering pipelines, and advanced analytical solutions. Our projects range from designing and implementing the latest data platform approaches (i.e. Lakehouse, DataOps, Data Mesh) using best practices and cloud solutions, building scalable data and ML pipelines, democratizing data through modern governance approaches, and delivering data products using advanced machine learning, visualization, and integration approaches.

You will act as the primary architect and technical lead on projects to scope and estimate work streams, architect and model technical solutions to meet business requirements, serve as a technical expert in client communications, and mentor junior project team members. On a typical day, you might expect to participate in design sessions, build data structures for an enterprise data lake or statistical models for a machine learning algorithm, coach junior resources, and manage technical backlogs and release management tools. Additionally, you will seek out new business development opportunities at existing and new clients.

WHO YOU ARE:
<ul>
<li>You have a minimum of 8+ years of technical, hands-on experience building, optimizing, and implementing data pipelines and architecture</li>
<li>Experience leading teams to wrangle, explore, and analyze data to answer specific business questions and identify opportunities for improvement</li>
<li>You are a highly driven professional and enjoy serving in a fast-paced, dynamic client-facing role where delivering solutions to exceed high expectations is a measure of success</li>
<li>You have a passion for leading teams and providing both formal and informal mentorship</li>
<li>You have strong communication and interpersonal skills, and the ability to engage customers at a business level in addition to a technical level</li>
<li>You have a deep understanding of data governance and data privacy best practices</li>
<li>You incorporate the usage of AI tooling, efficiencies, and code assistance tooling in your everyday workflows</li>
<li>You have a degree in Computer Science, Computer Engineering, Engineering, Mathematics, Management Information Systems or a related field of study</li>
<li>The ideal candidate will have recent technical knowledge of the following:</li>
<li><ul><li>Programming languages (e.g. Python, Spark, Java, C++, Scala, etc.)</li>
<li>SQL and NoSQL databases (MySQL, DynamoDB, CosmosDB, Cassandra, MongoDB, etc.)</li>
<li>Data pipeline and workflow management tools (Airflow, Dagster, AWS Step Functions, Azure Data Factory, etc.)</li>
<li>Stream-processing systems (e.g. Storm, Spark-Streaming, Pulsar, Flink, etc.)</li>
<li>Data Warehouse design (Databricks, Snowflake, Delta Lake, Lake formation, Iceberg)</li>
<li>MLOps platforms (Sagemaker, Azure ML, Vertex.ai, MLFlow)</li>
<li>Container Orchestration (e.g. Kubernetes, Docker Swarm, etc.)</li>
<li>Metadata management tools (Collibra, Atlas, DataHub, etc.)</li>
</ul></li><li>Experience with the data platform components on one or more of the following cloud service providers:</li>
<li><ul><li>AWS</li>
<li>Google Cloud Platform</li>
<li>Azure</li>
</ul></li>
</ul>Basic Qualifications
<ul>
<li>Thrive in a fast-paced, dynamic, client-facing role where delivering solid work products to exceed high expectations is a measure of success</li>
<li>Contribute in a team-oriented environment</li>
<li>Prioritize multiple tasks in order to consistently meet deadlines</li>
<li>Creatively solve problems in an analytical environment</li>
<li>Adapt to new environments, people, technologies and processes</li>
<li>Excel in leadership, communication, and interpersonal skills</li>
<li>Establish strong work relationships with clients and team members</li>
<li>Generate ideas and understand different points of view</li>
</ul><div>
Learn More: Credera is part of Omnicom Precision Marketing that delivers transformative solutions rooted in data, technology, and AI. Omnicom Precision Marketing delivers precisely targeted and meaningful customer experiences at scale. Using its universal framework of connected data, connected intelligence and connected experiences, OPM provides services that include data-driven product / service design, technology strategy and implementation, CRM / loyalty strategy and activation, econometric and attribution modelling, technical and business consulting and digital experience design and development.
Compensation: The salary range listed is provided for informational purposes only. Credera treats all applicants as individuals, considering, but not limited to, their professional and academic experience, specialized training, certifications, and associated responsibilities as they relate to our specific industry. The salary range listed is just one component of our total compensation package for each unique employee.

We believe in recognizing and rewarding contributions at every level. While senior-level employees are eligible for a variable component as part of their compensation package, we are committed to supporting the growth and development of all team members. As employees progress in their careers, everyone will have opportunities to take on new responsibilities and become eligible for additional rewards. We strive to create an environment where everyone is empowered to succeed and advance.

Benefits: Credera provides a competitive salary and a comprehensive benefits plan. Benefits include health, mental health, vision, dental, and life insurance, prescriptions, fertility and adoption benefits, community service days, paid parental leave, PTO, 14 paid holidays, matching 401(k), Healthcare &amp; Dependent Flexible Spending Accounts, and disability benefits. For more information regarding Omnicom benefits, please visit www.omnicombenefits.com.

Hybrid Working Model: Our employees have the flexibility to work remotely two days a week. We expect team members to spend three days in person, with the freedom to choose the days and times that best suit them, their project, and their teams. You'll collaborate with your project team to balance flexibility with the benefits of in-person connection, delivering outstanding results for our clients. The Why: In-person engagement is essential for building strong relationships with clients and colleagues. It fosters trust, encourages learning, and helps us grow as consultants and professionals.

Travel: For our consulting roles, our goal is to minimize travel, and most projects do not require extensive travel. While some projects may involve up to 80% travel for a period, the annual average for team members is typically 10%&ndash;30%. We take a personal approach to travel by considering your submitted preferences when assigning roles.

Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future; Credera will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT, or any other employment-based visa). 

All qualified applicants will receive consideration for employment without regard to race, color, religion, gender identity, sexual orientation, national origin, age, genetic information, veteran status, or disability.

Credera will never ask for money up front and will not use apps such as Facebook Messenger, WhatsApp or Google Hangouts for communicating with you. You should be very wary of, and carefully scrutinize, any job opportunity that asks for money prior to starting and/or one where all communications take place exclusively via chat.</div></div>

Senior Architect, Data

<div><div>Credera is a global consulting firm that combines transformational consulting capabilities, deep industry knowledge, AI and technology expertise to deliver valuable customer experiences and accelerated growth across various industries. We continuously evolve our services to meet the needs of future organizations and reflect modern best practices. Our unique global approach provides tailored solutions, transforming the most influential brands and organizations worldwide.

Our employees, the lifeblood of our company, are passionate about making an extraordinary impact on our clients, colleagues, and communities. This passion drives how we spend our time, resources, and talents. Our commitment to our people and work has been recognized globally. Please visit our employer awards page: https://www.credera.com/awards-and-recognition.</div>
We are looking for an enthusiastic Senior GenAI and LLM Architect to add to Credera's Data capability group. Our ideal candidate is excited about leading project-based teams in a client facing role to analyze large data sets to derive insights through machine learning (ML) and artificial intelligence (AI) techniques. They have strong experience in data preparation and analysis using a variety of tools and programming techniques, building and implementing models, and creating and running simulations. The Senior Architect should be familiar with the deployment of enterprise scale models into a production environment; this includes leveraging full development lifecycle best practices for both cloud and on-prem solutions across a variety of use cases.

You will act as the primary architect and technical lead on projects to scope and estimate work streams, architect and model technical solutions to meet business requirements and serve as a technical expert in client communications. On a typical day, you might expect to participate in design sessions, provision environments, and coach and lead junior resources on projects.

WHO YOU ARE:
<ul>
<li>8+ years of proven experience in the architecture, design, and implementation of large scale and enterprise grade AI/ML solutions, including hands-on statistical modeling and/or analytical experience in and industry or consulting setting</li>
<li>Master's degree in statistics, mathematics, computer science or related field (a PhD is preferred)</li>
<li>Experience with a variety of ML and AI techniques (e.g. multivariate/logistic regression models, cluster analysis, predictive modeling, neural networks, deep learning, pricing models, decision trees, ensemble methods, etc.)</li>
<li>Proficiency in programming languages such as Python, TensorFlow, PyTorch, or Hugging Face Transformers for model development and experimentation</li>
<li>Strong understanding of NLP fundamentals, including tokenization, word embeddings, language modeling, sequence labeling, and text generation</li>
<li>Experience with data processing using LangChain, data embedding using LLMs, Vector databases and prompt engineering</li>
<li>Advanced knowledge of relational and non-relational databases (SQL, NoSQL)</li>
<li>Proficient in large-scale distributed systems (Hadoop, Spark, etc.)</li>
<li>Experience with designing and presenting compelling insights using visualization tools (RShiny, R, Python, Tableau, Power BI, D3.js, etc.)</li>
<li>Passion for leading teams and providing both formal and informal mentorship</li>
<li>Experience with wrangling, exploring, transforming, and analyzing datasets of varying size and complexity</li>
<li>Knowledgeable of tools and processes to monitor model performance and data quality, including model tuning experience</li>
<li>Strong communication and interpersonal skills, and the ability to engage customers at a business level in addition to a technical level</li>
<li>Stay current with AI/ML trends and research; be a thought leader in AI area</li>
<li>Experience with implementing machine learning models in production environments through one or more cloud platforms:</li>
<li><ul><li>Google Cloud Platform</li>
<li>Azure cloud services</li>
<li>AWS cloud services</li>
</ul></li>
</ul>Basic Qualifications
<ul>
<li>Thrive in a fast-paced, dynamic, client-facing role where delivering solid work products to exceed high expectations is a measure of success</li>
<li>Contribute in a team-oriented environment</li>
<li>Prioritize multiple tasks in order to consistently meet deadlines</li>
<li>Creatively solve problems in an analytical environment</li>
<li>Adapt to new environments, people, technologies and processes</li>
<li>Excel in leadership, communication, and interpersonal skills</li>
<li>Establish strong work relationships with clients and team members</li>
<li>Generate ideas and understand different points of view</li>
</ul><div>
Learn More: Credera is part of Omnicom Precision Marketing that delivers transformative solutions rooted in data, technology, and AI. Omnicom Precision Marketing delivers precisely targeted and meaningful customer experiences at scale. Using its universal framework of connected data, connected intelligence and connected experiences, OPM provides services that include data-driven product / service design, technology strategy and implementation, CRM / loyalty strategy and activation, econometric and attribution modelling, technical and business consulting and digital experience design and development.
Compensation: The salary range listed is provided for informational purposes only. Credera treats all applicants as individuals, considering, but not limited to, their professional and academic experience, specialized training, certifications, and associated responsibilities as they relate to our specific industry. The salary range listed is just one component of our total compensation package for each unique employee.

We believe in recognizing and rewarding contributions at every level. While senior-level employees are eligible for a variable component as part of their compensation package, we are committed to supporting the growth and development of all team members. As employees progress in their careers, everyone will have opportunities to take on new responsibilities and become eligible for additional rewards. We strive to create an environment where everyone is empowered to succeed and advance.

Benefits: Credera provides a competitive salary and a comprehensive benefits plan. Benefits include health, mental health, vision, dental, and life insurance, prescriptions, fertility and adoption benefits, community service days, paid parental leave, PTO, 14 paid holidays, matching 401(k), Healthcare &amp; Dependent Flexible Spending Accounts, and disability benefits. For more information regarding Omnicom benefits, please visit www.omnicombenefits.com.

Hybrid Working Model: Our employees have the flexibility to work remotely two days a week. We expect team members to spend three days in person, with the freedom to choose the days and times that best suit them, their project, and their teams. You'll collaborate with your project team to balance flexibility with the benefits of in-person connection, delivering outstanding results for our clients. The Why: In-person engagement is essential for building strong relationships with clients and colleagues. It fosters trust, encourages learning, and helps us grow as consultants and professionals.

Travel: For our consulting roles, our goal is to minimize travel, and most projects do not require extensive travel. While some projects may involve up to 80% travel for a period, the annual average for team members is typically 10%&ndash;30%. We take a personal approach to travel by considering your submitted preferences when assigning roles.

Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future; Credera will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT, or any other employment-based visa). 

All qualified applicants will receive consideration for employment without regard to race, color, religion, gender identity, sexual orientation, national origin, age, genetic information, veteran status, or disability.

Credera will never ask for money up front and will not use apps such as Facebook Messenger, WhatsApp or Google Hangouts for communicating with you. You should be very wary of, and carefully scrutinize, any job opportunity that asks for money prior to starting and/or one where all communications take place exclusively via chat.</div></div>

Senior Architect, Data and GenAI

APGAR

<div>
 
 APGAR is a leading consultancy company specialized in
 
 Data Management
 
 and
 
 Artificial Intelligence
 
 , helping organizations across industries harness the power of data and AI to drive strategic and operational transformation.
 
 
 
 
 
 Your missions
 
 
 
 
 
 As an AI Solution Architect, you will be part of a team working on Client projects. You will be supervised by a Technical Director or a Manager and will act as a technical reference for AI-related topics.
 
 
 
 
 
 
 External missions
 
 :
 
 <ul>
 <li>
 You will work on all phases of AI and Data &amp; AI solutions delivery, from use case definition to production readiness
 </li>
 <li>
 You will take part in the design and definition of AI solution architectures (data flows, AI services, integration, security)
 </li>
 <li>
 You will define the technical approach for AI solutions (ML, Generative AI, RAG, predictive models) and validate implementation choices
 </li>
 <li>
 You will define operating rules, non-functional requirements, and scalability principles for AI solutions
 </li>
 <li>
 You will supervise and validate the implementation carried out by technical teams or partners
 </li>
 <li>
 You will be responsible for continuous integration, deployment, and monitoring principles for AI solutions (MLOps supervision)
 </li>
 <li>
 You will endorse responsibility for the overall technical quality of AI solutions and support the project team on complex technical topics
 </li>
 <li>
 You will be accountable for the overall quality of deliveries and technical documentation (architecture documents, security notes, operating guides)
 </li>
 <li>
 You will assist the client in the setup, administration, and governance of AI solutions in cloud or on-premise environments, while defining methodologies and DevOps/MLOps processes
 </li>
 </ul>
 
 
 
 
 
 Pre-sales
 
 :
 
 
 
 <ul>
 <li>
 You will be involved in effort estimation for tender calls
 </li>
 <li>
 You will write the technical and architectural sections of tender calls in full autonomy (writing and presentation)
 </li>
 <li>
 You will participate in client workshops and solution presentations to position AI solutions
 </li>
 </ul>
 
 
 
 
 
 R&amp;D and internal missions
 
 :
 
 <ul>
 <li>
 You will contribute to R&amp;D activities in collaboration with the Offers and Innovation teams
 </li>
 <li>
 You will participate in the design of reusable AI architectures, frameworks, and accelerators
 </li>
 <li>
 You will take part in technical knowledge capitalization (best practices, reference architectures, AI patterns)
 </li>
 <li>
 You will evaluate new AI platforms, tools, and cloud services to enrich our AI offerings
 </li>
 <li>
 You will participate in internal initiatives (mentoring, offers structuring, community of practice, recruitment support)Depending on your career path wishes and desires, you will have the opportunity to move towards a position of technico-functional consultant. While still acting as a functional consultant, you will also be involved in the setting and configuration of the solution.
 </li>
 </ul>
 
 
 
 
 Your Profile :
 
 <ul>
 <li>
 Master&rsquo;s degree or equivalent, with at least 5 &ndash; 8 years of experience in a consulting firm or IT services company
 </li>
 <li>
 You have designed, assessed, and guided the implementation of AI or advanced data solutions in enterprise environments
 </li>
 <li>
 You have strong experience in AI solution architecture and technical leadership
 </li>
 <li>
 You are comfortable working in client-facing and presales contexts
 </li>
 <li>
 You explained ML, GenAI, and Agentic AI concepts to non-technical stakeholders
 </li>
 <li>
 You communicated AI limitations, risks, and trade-offs clearly
 </li>
 <li>
 You have clearly written documentation and customer-facing summaries
 </li>
 <li>
 You participated in customer calls, demos, and workshops
 </li>
 <li>
 You did cross-functional communication with product, engineering, and sales teams
 </li>
 </ul>
 
 
 
 
 You have a solid grasp of the following fields:
 
 
 Core AI &amp; Machine Learning
 
 <ul>
 <li>
 Understanding of machine learning fundamentals (supervised/unsupervised learning, model training, evaluation)
 </li>
 <li>
 Familiarity with common ML algorithms (regression, classification, clustering)
 </li>
 <li>
 Basic understanding of feature engineering and data preprocessing
 </li>
 <li>
 Ability to interpret ML model outputs and performance metrics (accuracy, precision/recall, F1, etc.)
 </li>
 <li>
 Awareness of model overfitting, bias, and generalization
 </li>
 <li>
 Understanding of model lifecycle (training, validation, deployment, monitoring)
 </li>
 </ul>
 
 Data &amp; Integration
 
 <ul>
 <li>
 Data architectures (data lake, lakehouse, batch &amp; streaming)
 </li>
 <li>
 Data integration patterns, APIs, and enterprise systems
 </li>
 <li>
 Data quality, metadata, and governance concepts
 </li>
 </ul>
 
 Cloud &amp; Platforms
 
 <ul>
 <li>
 Strong exposure to Azure, AWS, or GCP ecosystems
 </li>
 <li>
 Managed AI services and vector databases
 </li>
 <li>
 Security, identity management, and access control
 </li>
 </ul>
 
 Architecture &amp; Documentation
 
 <ul>
 <li>
 Design of technical and solution architecture documents
 </li>
 <li>
 Definition of operating models and deployment strategies
 </li>
 <li>
 Ability to review and challenge technical designs
 </li>
 </ul>
 
 Methodology &amp; Delivery
 
 <ul>
 <li>
 Agile delivery methodologies
 </li>
 <li>
 CI/CD and MLOps concepts (deployment, monitoring, retraining)
 </li>
 <li>
 Experience working with tools such as Jira, Git-based workflows, and CI pipelines
 </li>
 </ul>
 
 AI-Readiness &amp; Enablement
 
 <ul>
 <li>
 Assessing customer AI-readiness (data availability, quality, governance, risk)
 </li>
 <li>
 Identifying AI-appropriate use cases based on customer maturity
 </li>
 <li>
 Supporting customers in preparing data and workflows for ML and GenAI adoption
 </li>
 <li>
 Educating customers on responsible AI and realistic expectations
 </li>
 <li>
 Contributing to AI-readiness assessments, frameworks, or playbooks
 </li>
 </ul>
 
 
 
 
 
 
 
 Do not hesitate to apply if you are a dynamic, enthusiastic and curious person. You will join a pleasant, benevolent and fraternal working environment&hellip; Future Apgarians, we are waiting for you!
 
</div>

AI Solution Consultant

Streamline Healthcare Solutions

<div>Job Description:
<div>About Streamline Healthcare Solutions
</div><div><div><div><div><div><div><div><div><div>Here at Streamline, we strive on building lasting and trusting relationships with our clients, and our employees set the bar.
Streamline&rsquo;s mission is to build innovative technology solutions that empower people who improve behavioral health and quality of life of those in need. We are a high growth technology company that delivers web-based software for healthcare organizations to provide and coordinate all service delivery processes. Streamline has been offering software in the behavioral health marketplace since 2003. Streamline has built and maintains systems for some of the nation&rsquo;s premier behavioral health organizations using the latest web-based technology.
Streamline offers competitive compensation and benefits packages as well as a challenging, yet flexible, work environment that is conducive to collaboration and productivity. A career with Streamline Healthcare Solutions provides opportunities for growth and continued learning in a workplace where individual contribution is valued and recognized. Join us, and advance your career today with a company that is on the cutting edge of the behavioral healthcare technology industry.
Summary of the AI Architect
</div></div></div></div></div></div></div></div></div>The AI Architect owns the enterprise AI architecture, standards, and governance for healthcare-grade solutions&mdash;establishing reference patterns, platforms, and guardrails that product teams use to safely and efficiently deliver LLM applications, RAG systems, and ML services. This role partners with Security/Compliance, Data/Platform, and Product leaders to ensure HIPAA-aligned handling of PHI/PII, Responsible AI practices, and measurable clinical and business outcomes. The ideal candidate brings deep Azure experience (including Azure AI Foundry / Azure AI Studio), broad knowledge of OpenAI or Anthropic models, and proven enterprise architecture leadership.
This position is remote and based in the United States. The salary range is $150,000 - $200,000, DOE. Employment visa sponsorship is not available for this role.
Responsibilities of the AI Architect
Enterprise Architecture &amp; Standards
<ul><li>Define and maintain reference architectures for LLM applications, RAG patterns, classical ML, and AI-enabled services across the organization.
</li><li>Establish solution blueprints for embeddings/vector search, prompt orchestration, guardrails/safety layers, evaluation frameworks, lineage, and observability.
</li><li>Publish SLO/SLA templates, token/GPU budget rules, multi-tenancy/isolation approaches, and cost governance playbooks.
</li></ul>Platform &amp; Tooling
<ul><li>Own platform and tooling selection for Azure AI (Azure AI Foundry/Studio, Azure OpenAI, Azure AI Search, Azure ML), Databricks (Delta Lake, MLflow), and orchestration (Airflow or Azure Data Factory).
</li><li>Define standard patterns for vector databases (e.g., Azure AI Search, Pinecone, FAISS), feature store usage, and data ingestion/streaming.
</li><li>Provide reference implementations and reusable accelerators (RAG starter kit, evaluation harness, prompt library, safety policies).
</li></ul>Security, Compliance &amp; Responsible AI
<ul><li>Embed PHI/PII safeguards and HIPAA-aligned controls into SDLC and CI/CD gates; standardize data boundaries, de-identification/anonymization (e.g., Presidio), Key Vault, encryption, RBAC, and auditability.
</li><li>Define and operationalize Responsible AI requirements (bias/fairness evaluations, model cards, data sheets, red-teaming) as release criteria.
</li><li>Partner with Security/Compliance on risk assessments, release approvals, and policy updates; review high-risk use cases
</li></ul>Solution Governance &amp; Reviews
<ul><li>Lead the AI Architecture Review process; manage deviations from standards with an exception register and migration plans.
</li><li>Advise squads on prompt design, tool/function calling, grounding/RAG strategies, evaluation design (hallucination, safety, utility), and observability (latency, accuracy, drift, cost).
</li></ul>Collaboration &amp; Enablement
<ul><li>Collaborate with Lead AI Software Engineers, data scientists, and platform teams to land architectures in production.
</li><li>Mentor teams in Azure AI Foundry, OpenAI/Anthropic model usage, Microsoft Copilot, and GitHub Copilot&mdash;including governance and data leakage prevention.
</li><li>Run communities of practice, internal training, and publish architecture decision records (ADRs) and technical standards.
</li></ul>Education and Experience Requirements for the AI Architect
<ul><li>Bachelor&rsquo;s degree in Computer Science, Information Technology, Computer Information Systems, Health Informatics, or a related field.
</li><li>10+ years in software/solution architecture with 5+ years in AI/ML systems and 2+ years leading enterprise AI architecture or platform initiatives.
</li><li>Enterprise cloud architecture (Azure): Azure AI Foundry (Azure AI Studio), Azure OpenAI, Azure AI Search, Azure ML, Azure Key Vault, networking/IAM, encryption, logging/monitoring.
</li><li>Hands-on architectural experience with OpenAI or Anthropic models (e.g., GPT‑4.x/4o, Claude 3.x): prompt &amp; tool calling patterns, grounding/RAG, evaluation methodologies.
</li><li>Demonstrated Responsible AI leadership: guardrails, safety filters, bias/fairness evaluations, model cards/datasheets, and red-teaming processes.
</li><li>Security &amp; privacy familiarity: PHI/PII protections and HIPAA-aligned design patterns; ability to translate policy into technical controls and CI/CD checks.
</li><li>Data platform fluency: Databricks (Delta Lake, MLflow), Spark, orchestration (Airflow or Azure Data Factory/Synapse), and data governance (e.g., Purview).
</li><li>MLOps standards: model registry, CI/CD for ML, environment isolation, canary/A/B testing, drift/performance/cost monitoring, rollback strategies.
</li><li>Strong understanding of SQL Server data modeling and performance; able to guide teams using SSMS and review T‑SQL patterns for AI data workloads.
</li><li>Familiarity with Visual Studio and .NET integration patterns to ensure AI services fit the enterprise application ecosystem.
</li><li>Experience enabling secure, governed use of Microsoft Copilot and GitHub Copilot in engineering workflows.
</li><li>Excellent communication and influence skills; proven success leading architecture reviews and driving cross-functional decisions.
</li></ul>Preferred Education and Experience Requirements for the AI Architect
<ul><li>Healthcare domain knowledge (clinical or revenue cycle management): FHIR/HL7, EHR/claims data integration, and clinical NLP (entity extraction, summarization, coding/RCM use cases).
</li><li>Inference optimization: GPU/CUDA, quantization/distillation, caching strategies, prompt/token budgeting, multi-tenant cost control.
</li><li>Security/compliance certifications (e.g., HCISPP, CISSP) or demonstrable leadership in healthcare-grade architectures.
</li><li>Track record of creating reusable accelerators/libraries/platform capabilities adopted across multiple teams.
</li><li>Governance &amp; ethics: model cards, datasheets for datasets, bias/fairness evaluations, and red-teaming.
</li><li>Familiarity with .NET microservices and API design to integrate AI services into enterprise systems. 
</li></ul> 
Streamline Healthcare Solutions is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, disability, military status, national origin, or any other characteristic protected under federal, state, or applicable local law.</div>

AI Architect

Capital One

<div>Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology)<div><div><div><div><div><div><div><div><div>
As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You&rsquo;ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You&rsquo;ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.
Enterprise Platforms Technology (EPTech) comprises many of Capital One&rsquo;s most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices.
What you&rsquo;ll do in the role:<ul><li>
The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:</li><li>
Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.</li><li>
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).</li><li>
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.</li><li>
Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.</li><li>
Retrain, maintain, and monitor models in production.</li><li>
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.</li><li>
Construct optimized data pipelines to feed ML models.</li><li>
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.</li><li>
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.</li><li>
Use programming languages like Python, Scala, or Java.</li></ul>
Basic Qualifications:<ul><li>
Bachelor&rsquo;s degree</li><li>
At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)</li><li>
At least 4 years of experience programming with Python, Scala, or Java</li><li>
At least 3 years of experience building, scaling, and optimizing ML systems</li><li>
At least 2 years of experience leading teams developing ML solutions</li></ul>
Preferred Qualifications:<ul><li>
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field</li><li>
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>
4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow</li><li>
3+ years of experience developing performant, resilient, and maintainable code</li><li>
3+ years of experience with data gathering and preparation for ML models</li><li>
3+ years of people management experience</li><li>
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents</li><li>
3+ years of experience building production-ready data pipelines that feed ML models</li><li>
Ability to communicate complex technical concepts clearly to a variety of audiences</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
</div></div></div></div></div></div></div></div></div>The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div>

Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology)

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