Machine Learning Solution Architect Job at Provectus

Machine Learning Architect

We are expanding our team of motivated technologists with a proven track record ...

Location

United States , Remote; San Diego; San Francisco; Irvine; Los Angeles

Salary:

153000.00 - 244700.00 USD / Year

Rackspace

Expiration Date

Until further notice

Requirements

Masters with 10+ years of experience or PhD with 6+ years of experience in Machine Learning, Natural Language Processing (NLP) and Deep Learning
Minimum 5+ years of experience architecting and building Machine Learning solutions
Minimum 5+ years of experience with cloud platforms (AWS, GCP, Azure)
Experience building ML models and strong knowledge of ML techniques is required
Experience with hugging face, TensorFlow/pytorch, transformer architectures, prompt engineering, agentic systems, LLMs
Strong coding experience in Python and architectural patterns like microservices
Solid understanding of agile methodologies and experience in planning machine learning projects from inception to production deployment
Strong problem-solving skills and the ability to lead a team on “what’s next” when encountering a technical issue in a machine learning project
Excellent communication and presentation skills, with the ability to explain complex technical concepts to both technical and non-technical audiences

Job Responsibility

Design machine learning solutions and execute machine learning projects end to end from proof-of-concept stage to deployment in production using cloud native technologies and state of the art machine learning models
Be technically focused but work directly with the business representatives/customers to understand the requirements driving the need for a solution to be developed
Be responsible for all phases of the project from problem definition, data annotation, model development, model deployment to end user documentation/training
Design the architecture of ML solutions on cloud platforms (AWS, Azure, GCP) including MLOPs
Stay abreast of the latest developments. Read the latest published machine learning research and adapt the models to solve customer’s problems
Establish credibility by demonstrating technical excellence and delivering value through solutions you build. Develop strong relationships with our customers

What we offer

Based on eligibility, compensation for the role may include variable compensation in the form of bonus, commissions, or other discretionary payments

Fulltime

Machine Learning Hardware Architect

In this position you will work with Machine Learning Hardware Architects, Digita...

Location

United States , Sunnyvale

Salary:

212000.00 - 294000.00 USD / Year

Sr. Specialist Solutions Architect, High Performance Computing and Machine Learning

AWS Worldwide Specialist Solutions Architects (SSAs) are technologists with deep...

Location

Singapore , Singapore

Salary:

Not provided

Amazon

Expiration Date

Until further notice

Requirements

8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
3+ years of design, implementation, or consulting in applications and infrastructures experience
10+ years of IT development or implementation/consulting in the software or Internet industries experience

Job Responsibility

Design Customer Solutions – Collaborate with the wider AWS teams to help customers and partners architect HPC Solutions that leverage AWS Services
Engage with Solution Architects, Account Managers, Professional Services, and Partners to define an HPC Engagement strategy for AWS operational territories and key accounts, with emphasis on public sector National Super Computing Centers, Government agencies, and/or AI/ML, CAE, Weather and accelerated computing with GPU
Thought Leadership – Provide thought leadership on solutions that benefit customers through the use of AWS Services
Serve as a key member of the business development and accounting management team in helping to ensure customer success in building and migrating applications, software and services on the AWS platform
Assist solution providers with the definition and implementation of technical and business strategies
Capture and share best-practice knowledge amongst the worldwide AWS solution architect community
Understand AWS market segments, and industry verticals
Understand and exploit the use of internal business support systems

Fulltime

Machine Learning Software Engineer

In this role, you will design, build, and optimize robust ML models, data pipeli...

Location

Canada , Calgary

Salary:

Not provided

Randstad

Expiration Date

August 08, 2026

Requirements

BSc. or MSc. degree in Computer Science, Engineering, Mathematics, Physics, Statistics, or an equivalent quantitative discipline
Minimum of 3+ years of professional experience successfully delivering AI/ML projects
Minimum of 2+ years operating explicitly as a software developer within a structured delivery team
Mastery of ML algorithms, techniques, and Agentic frameworks, with the proven ability to optimize models with minimal supervision
Advanced expertise in at least two common development languages (e.g., Python, Java, C#)
Proficient working knowledge of general Python data packages and relational/non-relational databases and query engines (e.g., SQL)
Strong foundational knowledge of DevOps automation practices and building production solutions within AWS
Proficient with statistical concepts and capable of applying rigorous statistical thinking to solve complex business problems

Job Responsibility

Build, optimize, and scale machine learning models and end-to-end data pipelines
Design and implement critical operational aspects of model deployment, including automation pipelines, continuous monitoring, and automated drift detection
Transition experimental models and prototypes into robust, maintainable, and production-grade software applications
Participate in research experiments and rapid prototyping to validate next-generation AI concepts
Provide core software engineering expertise to internal data analytics and data science delivery teams
Apply strict software development best practices, including Test-Driven Development (TDD) and automated CI/CD workflows
Review requirements, map system dependencies, and provide accurate implementation effort estimations during team planning sessions
Test, debug, and optimize application code to eliminate performance bottlenecks
Conduct thorough code reviews and provide constructive feedback to elevate overall team code quality
Collaborate closely with architects, data scientists, product teams, and business stakeholders to translate high-level goals into functional ML architectures

What we offer

Cutting-Edge AI Scope: Direct involvement in building and optimizing both traditional ML models and next-generation Agentic solutions with a high degree of autonomy
End-to-End Technical Ownership: Lead the operational deployment (MLOps) of AI models, directly influencing infrastructure automation, model tracking, and system performance
Cross-Functional Collaboration: Serve as the technical software anchor within a diverse ecosystem of data scientists, enterprise architects, and product managers
Modern Cloud Stack: Deepen your expertise in cloud-native deployment using AWS, enterprise data pipelines, and advanced platforms like Databricks

Senior Machine Learning Engineer – AV Labs

Uber is launching AV Labs to accelerate the autonomous technology ecosystem. We'...

Location

United States , Sunnyvale

Salary:

202000.00 - 224000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

4+ years of working experience in the ML/Robotics industry
Bachelor's degree in Computer Science, Computer Engineering, or related fields
Proficient in Python and Linux environments
Familiar with modern AI/ML frameworks (e.g., PyTorch).

Job Responsibility

Algorithm Development: Lead the development of autonomy algorithms and foundation models that extract high-fidelity semantic meaning from complex urban edge cases to enrich our L4 data lake
Systems Architecture Design: Architect scalable ML systems, including management of upstream sensor dependencies
Technical Leadership: Partner with fellow engineers to architect, design, and build scalable solutions for ML technology that can stand the test of scale and availability
Dataset Optimization: Deliver high-quality datasets to accelerate ML technologies through advanced sensor data collection, processing, and auto-labeling
Cross-Functional Collaboration: Partner with platform, product, and security engineering teams to enable the successful deployment of the latest machine learning techniques into production.

What we offer

Bonus program
Equity award & other types of comp
401(k) plan
Various benefits

Fulltime

Senior Cloud Solution Architect

With over 17,000 employees worldwide, the mission of the Customer Experience & S...

Location

United States , Multiple Locations

Salary:

106400.00 - 203600.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's degree in computer science, Information Technology, Engineering, Business or related field AND 4+ years' experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or Business Applications consulting OR equivalent experience
Breadth of technical experience and knowledge in foundational security, foundational AI, architecture design, with depth / Subject Matter Expertise in one or more of the following: Deep Domain Expertise in Azure AI Areas: Deep domain expertise in one or more of the Azure AI specific areas, such as Cognitive Services, Azure OpenAI, AI Agents, Microsoft Foundry and Copilot Studio OR hands-on experience working with the respective products at the expert level. Expertise with Azure AI Search and/or Vector Indexes, Azure Document Intelligence, Azure Content Understanding and /or equivalent OCR technology
Programming Languages and Integration: Proficient with Python, C#, R, JavaScript, or similar programming languages in the context of application development, and ability to integrate Azure AI with other services (e.g., Azure Functions, Azure Container Apps, Docker, API Management, MCP servers)
Architecting Enterprise-Grade Solutions: The ability to create and explain 3-tier architecture diagrams, system context diagrams, system interaction diagrams, etc.
Proven experience building enterprise-grade, AI-focused solutions on the cloud (Azure, AWS, GCP) for customers, from Minimum Viable Products (MVPs) leading to production deployments
Infrastructure as Code (IaC) Deployment: Strong understanding of Bicep, Terraform, or Azure Resource Manager and familiarity with configuration and deployment of IaC templates in a secure environment
Core AI & ML Concepts: Familiarity with AI & ML foundational knowledge of concepts like Prompt Engineering, RAG, Agentic Orchestration, tools (Jupyter notebooks & VS Code)
GenAIOps & DevOps: Familiarity with CI/CD pipelines (GitHub Actions, Azure DevOps), Prompt and Model Evaluation, AI Harnesses (e.g., evaluation, orchestration), and observability for general Azure workloads using Application Insights, Azure Monitor, OpenTelemetry and/or other Observability tools
Agentic Workflows: Familiarity with Agent Framework, MCP, Langchain, or other agentic frameworks. Ability to configure tools for dynamic execution by an LLM
Generative AI and Responsible AI: Knowledge of current and emerging AI technology, including Generative AI technology applications and use cases (including, but not limited to, Large Language Models) and Foundational models toolsets

Job Responsibility

Play a pivotal role in the AI Factory, providing technical enablement, operational support, and strategic engagement across customer projects. This role is designed to ensure successful delivery of AI solutions, troubleshoot complex issues, and support innovation through pilot evaluations and advanced use case development. Understand customers' overall data estate, business priorities, and IT success measures. Innovate with AI solutions that drive business value
Facilitate scalable delivery through strong technical program management utilizing a factory model/approach, driving program awareness and demand across the regional operating units. Attend in-flight project status meetings to monitor progress and identify support needs. Engage directly with complex or non-standard customer use cases beyond existing accelerators. Participate in intake reviews for milestone sizing, objection handling, and technical scoping
Ensure Solution Excellence: Deliver solutions with high performance, security, scalability, maintainability, repeatability, reusability, and reliability upon deployment. Gather insights from customers and partners
Drive Consumption Growth: Develop opportunities to enhance Customer Success and help customers extract value from their Microsoft investments
Operational Awareness: Understanding of consumption metrics and their reflection on program effectiveness. Ability to collaborate with local teams for nominations and intake support
Unblock Customer Challenges: Leverage subject matter expertise to identify resolutions for customer blockers. Follow best practices and utilize repeatable IP
Identify and contribute repeatable IP and assets that create velocity in deployment and drives customer value from their Unified investment. Continuously look to improve upon these assets utilizing the best of field inputs. Evaluate pilot opportunities for potential integration into existing offerings
Architect AI Solutions: Apply technical knowledge to design solutions aligned with business and IT needs. Create Innovate with AI roadmaps, lead POCs and MVPs, and ensure long-term technical viability
Advocate for Customers: Share insights and best practices, collaborate with the Factory team to address key blockers, and influence improvements, roadmap and feature prioritization
Resolve technical blockers: Debug technical issues and provide fixes for engagements encountering blockers

Fulltime

AI/Gen Ai Solution Architect

DXC Technology is looking for AI/Gen AI Solution Architect to join Analytics Off...

Location

Italy , Milan

Salary:

48000.00 EUR / Year

DXC Technology

Expiration Date

Until further notice

Requirements

At least 5 years of experience in designing and developing AI solutions
Experience with machine learning frameworks and tools
Strong communication and presentation skills, with the ability to effectively convey complex technical concepts to non-technical stakeholders

Job Responsibility

Design AI solutions by collaborating with clients to understand their business requirements and challenges
Leading the development and implementation of AI solutions, including machine learning models, natural language processing, and computer vision applications
Work closely with our sales team to support presales activities, including creating technical proposals, presenting solutions to clients and providing guidance on implementation strategies
Staying up-to-date on the latest trends and developments in the AI field, and leveraging this knowledge to drive innovation in our solutions

What we offer

Health Insurance
Permanent disability by accident coverage
Life and permanent disability by accident coverage
Meal vouchers
Supplemental Pension Plan
Smart Working Agreement
Employee Discounts Program
Continuous Learning Access learning platforms and take part in skill development programs designed for you
Refer & Earn Help us find great talent through the Employee Referral Program and get rewarded for your contribution
Career Development DXC promotes professional growth and internal mobility by making every open position accessible to all employees. Through the Performance Development program, the company supports individual aspirations to achieve shared goals together

Fulltime

Senior Machine Learning Engineer

Join Amgen’s Mission of Serving Patients. At Amgen, if you feel like you’re part...

Location

United States , Thousand Oaks

Salary:

158606.00 - 200052.00 USD / Year

Amgen

Expiration Date

Until further notice

Requirements

Bachelor’s degree (or foreign equivalent) in Computer Science, Statistics, Electrical Engineering, Mathematics, Bioengineering or a related field and 4 years of experience in the job offered or in a Data Scientist related – Occupation
4 years of experience in the following: 1) Programming skills in Python including experience with scientific computing and machine learning libraries including pandas, NumPy, scikit-learn, XGBoost, LightGBM, TensorFlow and PyTorch
2) Applying supervised and unsupervised learning techniques to real-world problems, including experience with Random Forest, XGBoost, ensemble models, and deep learning architectures
3) Version control (Git), containerization and orchestration tools including Docker and Kubernetes, and cloud environments including AWS or GCP
4) Involved with data science platforms including Databricks and SageMaker
5) Using statistical methods industry including regression modeling, hypothesis testing, Bayesian methods, Forecasting techniques and time-series analysis
6) Building ETL (Extract, Transform, Load) pipelines for handling large-scale, high-dimensional datasets, familiarity with healthcare data structures and data types
7) Experience with software DevOps CI/CD tools and GitLab
8) Experience developing and fine-tuning Natural Language Processing (NLP) models, including work with architectures such as BERT, ALBERT, GPT, and other transformer-based models.

Job Responsibility

Lead efforts with Amgen business leaders to identify, explore and develop transformative AI and ML solutions to enable access to computational tools and data within Amgen, and ultimately improve patient outcomes across multiple therapeutic areas
Utilize Cloud Services to collect, store, preprocess, and analyze large datasets from various sources across Amgen
Collaborate with other ML engineers, data scientists and research scientists to identify appropriate ML models and algorithms
Facilitate ML & Data engineering efforts by architecting and guiding the implementation of data and ML pipelines for development and deployment
Facilitate model deployment to production, including monitoring and maintenance of ML models, put in place metrics to assess accuracy and drift
Define model evaluation and validation strategies, train and test models, and analyze and resolve errors and biases in models
Lead and develop standards, processes, and best practices for the team across the machine learning-based solution implementation lifecycle
Involved in technical guide and career development mentor to junior machine learning engineers and data scientists in a formal or matrixed fashion.

What we offer

stock
retirement
medical
life and disability insurance
eligibility for an annual bonus or for sales roles, other incentive compensation
Retirement and Savings Plan with generous company contributions
group medical, dental and vision coverage
life and disability insurance
flexible spending accounts
discretionary annual bonus program

Fulltime

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Machine Learning Solution Architect

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