machine learning specialist

G2i Inc.

<div><p><b>Machine Learning Evaluation Specialist (Remote)</b></p><p><b>
List of accepted countries and locations</b></p><p><b>
Important for US applicants: This is a 1099 independent contractor role and is not compatible with F-1 OPT, STEM OPT, or other visa statuses that require W-2 employment, guaranteed hours, or employer sponsorship. We are unable to provide offer letters or employment verification for this role.</b></p><p></p><p><i>
Help design the hardest ML problems state-of-the-art AI hasn't solved yet.</i></p><p>
We're hiring domain experts to build evaluation tasks that challenge the frontier of AI. This is not an ML engineering role &mdash; it's a research role. You'll use deep expertise in your field to create problems that general ML knowledge can't touch.</p><p></p><p><b>
What you'll do</b></p><ul><li><p>
Propose and frame original, research-grade ML problems rooted in your domain</p></li><li><p>
Design evaluation tasks that require specialized knowledge well beyond standard pipelines</p></li><li><p>
Assess AI-generated solutions for correctness, creativity, and methodological rigor &mdash; and explain exactly where and why they fall short</p></li><li><p>
Document problem difficulty, required domain knowledge, and expected failure modes</p></li></ul><p></p><p><b>
What you need</b></p><ul><li><p>
Graduate-level expertise (MS or PhD preferred) in a scientific or technical domain that intersects with ML</p></li><li><p>
Strong working knowledge of ML methods &mdash; model selection, feature engineering, evaluation metrics</p></li><li><p>
Deep familiarity with active research problems in your field &mdash; you know where general ML knowledge runs out</p></li><li><p>
Excellent written communication &mdash; you can articulate complex problems clearly and precisely. This cannot be overstated.</p></li><li><p>
Self-motivated and comfortable working independently on intellectually demanding tasks</p></li></ul><p></p><p><b>
What you don't need</b></p><ul><li><p>
No prior AI training or RLHF experience required</p></li><li><p>
No software engineering background needed &mdash; domain expertise and research instincts are what matter</p></li></ul><p></p><p><b>
Domains we're especially looking for</b></p><ul><li><p>
Computational Biology / Bioinformatics</p></li><li><p>
Genomics / Molecular Biology</p></li><li><p>
Physics / Astrophysics / Signal Processing</p></li><li><p>
Climate / Environmental Modeling</p></li><li><p>
Healthcare / Medical Imaging</p></li><li><p>
Neuroscience / Brain-Computer Interfaces</p></li><li><p>
Materials Science / Chemistry</p></li><li><p>
Finance / Quantitative Modeling</p></li><li><p>
Robotics / Control Systems / Reinforcement Learning</p></li><li><p>
Advanced NLP (specialized domains)</p></li><li><p>
Mathematics / Statistics (applied)</p></li></ul><p></p><p><b>
Logistics</b></p><ul><li><p>
Fully remote &mdash; work from anywhere</p></li><li><p>
$200&ndash;$400/hr depending on domain and seniority</p></li><li><p>
10&ndash;40 hrs/week, hourly contract</p></li><li><p>
Assessment required &mdash; paid if approved</p></li><li><p>
Independent contractor (1099) &mdash; not compatible with F-1 OPT, STEM OPT, or visa statuses requiring W-2 employment or employer sponsorship</p></li></ul><p></p><p>
This is a project-based, freelance opportunity with no guaranteed hours. We recommend keeping other work options open while waiting for project assignment.</p></div>

Machine Learning Evaluation Specialist - Remote

Amazon Web Services

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Are you passionate about Machine Learning, Deep Learning, and Artificial Intelligence? Join AWS as a Generative AI and Machine Learning Specialist Solutions Architect in the MENAT region, where you'll drive cutting-edge AI initiatives and business transformation. As a Subject Matter Expert for designing machine learning solutions, you'll leverage AWS services to automate solutions and reduce costs for customers.
<br>
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You'll partner closely with GenAI/ML specialist sales teams along with field teams to enable large-scale customer use cases and drive adoption of AWS GenAI/ML solutions. Your expertise will shape machine learning architectures, develop technical assets, and create field enablement materials that help other Solutions Architects integrate AWS GenAI/ML solutions into customer environments. This role offers an exciting opportunity to be at the forefront of GenAI innovation in a region implementing numerous transformative AI initiatives.<br>
<br>
Key job responsibilities<br>
<ul><li>Design and architect scalable, secure, and innovative GenAI solutions that leverage AWS services to solve complex customer challenges and drive business transformation.</li><li>Build and maintain technical trusted advisor relationships with influential technical decision makers for successful adoption and deployment of AWS GenAI/ML services and technologies.</li><li>Evangelize current and future AWS GenAI and ML services through white papers, blogs, reference implementations, and presentations to enable customers and partners.</li><li>Capture and share best-practice knowledge amongst the AWS solutions architect community, creating field enablement materials for the broader SA population.</li><li>Work collaboratively with sales teams to create and execute business plans that accelerate AWS adoption, exceed revenue goals, and drive customer satisfaction with GenAI/ML solutions.</li></ul><br>
A day in the life<br>
Your day begins with a technical deep dive with a customer's AI team to understand their GenAI requirements and propose architecture solutions using Amazon Bedrock and SageMaker. Later, you'll collaborate with sales colleagues on business plans for driving AI adoption, then spend time developing a reference architecture for a RAG solution that addresses common customer needs. You might finish by drafting a technical blog on implementing ML solutions or conducting a workshop to demonstrate AI capabilities to potential customers.<br>
<br>
About the team<br>
You'll join AWS's innovative team in the MENAT region where numerous AI initiatives are being driven. As part of the AGS MENAT Specialist organization, you'll work alongside talented technical professionals who are transforming how businesses leverage AI technologies. The team fosters an inclusive culture that values continuous learning and professional growth, providing opportunities to collaborate on groundbreaking projects that shape the future of AI adoption across diverse industries in the region.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><p>
- - Bachelor's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree and 5+ years of professional or military experience<br>
- - 10+ years of working with Data &amp; AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience<br>
- - Experience building services using AWS products<br>
- - Experience with large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and agentic workflows.<br>
- - Proficiency in Python and experience with GenAI frameworks (LangChain, LlamaIndex, etc.) and model APIs.<br>
- - Experience participating in the sales lifecycle (directly or indirectly) for GenAI solutions.<br>
- - Experience in leading executive briefings and customer workshops focused on GenAI strategy, use case development, and prototype demonstrations.</p><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><p>
- - Master's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or PhD<br>
- - Experience prioritizing competing demands, scoping large efforts, and negotiating timelines<br>
- - Experience with enterprise-scale infrastructure or development-based cloud programs/projects in a related industry<br>
- - Experience conveying complex technical concepts to both technical and business audiences<br>
- - Publications or presentations in recognized GenAI, NLP, or ML journals or conferences.<br>
- - Hands-on experience architecting and deploying production GenAI solutions in secure or regulated environments.<br>
- - Deep technical expertise with AWS GenAI services including Amazon Bedrock (Claude, Llama, Titan models), Amazon SageMaker JumpStart, Amazon Q, and related AWS services (Lambda, Step Functions, ECS/EKS, API Gateway).<br>
- - Experience with GenAI security patterns, responsible AI practices, and model governance.<br>
- - Ability to collaborate with global/enterprise account sales and delivery teams to drive adoption of GenAI Solutions into top accounts.<br>
- - Ability to think strategically about business, product, and technical problems in the GenAI space and develop strategic, data-driven approaches.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</p></div>

Solutions Architect III, AGS MENAT Specialist Team

CapTech

<div>
 <p>
  CapTech is an award-winning consulting firm that collaborates with clients to achieve what&rsquo;s possible through the power of technology. At CapTech, we&rsquo;re passionate about the work we do and the results we achieve for our clients. From the outset, our founders shared a collective passion to create a consultancy centered on strong relationships that would stand the test of time. Today we work alongside clients that include Fortune 100 companies, mid-sized enterprises, and government agencies, a list that spans across the country.
  <br/>
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 </p>
 <p>
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 </p>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 <p>
  CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.
  <br/>
  <br/>
 </p>
 <p>
  <strong>
   <em>
    Specific responsibilities for the Machine Learning Engineer position include:
    <br/>
    <br/>
   </em>
  </strong>
 </p>
 <ul>
  <li>
   Strategizing with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs
  </li>
  <li>
   Deconstructing client needs into data-driven processes/models and analytical measures.
  </li>
  <li>
   Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).
  </li>
  <li>
   Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).
  </li>
  <li>
   Productionizing ML systems with a focus on optimization and scalability to satisfy clients&rsquo; requirements.
  </li>
  <li>
   Growing CapTech&rsquo;s Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers.
  </li>
 </ul>
 <p>
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  <br/>
  <br/>
  <br/>
 </p>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree or equivalent combination of education and experience.
  </li>
  <li>
   Hands-on experience manipulating and analyzing large (multi-billion record) data sets.
  </li>
  <li>
   Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.
  </li>
  <li>
   Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
  </li>
  <li>
   Proficiency with containerization (e.g., Docker) and microservices.
  </li>
  <li>
   Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS
  </li>
  <li>
   Comfort and proficiency in framing data-driven problems from cross-industry business requirements.
  </li>
  <li>
   Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)
  </li>
  <li>
   Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).
  </li>
  <li>
   Knowledge of DevOps and automation best practices.
  </li>
  <li>
   Knowledge of statistics and statistical modeling methods.
  </li>
  <li>
   Knowledge of model management and model versioning best practices.
  </li>
  <li>
   Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production setting
  </li>
  <li>
   Experience with prompt engineering, MCP and RAG, and agentic AI architectures
  </li>
  <li>
   Strong understanding of conversational UX and prompt evaluation metrics
  </li>
  <li>
   Experience with agentic frameworks in practice (langchain, n8n, pydantic, etc.)
  </li>
  <li>
   Experience with multi-agent orchestration
  </li>
 </ul>
 <p>
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 </p>
 <p>
  <br/>
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 </p>
 <strong>
  Additional Information
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 </strong>
 <p>
  We want everyone at CapTech to be able to envision a lasting and rewarding career here, which is why we offer a variety of career paths based on your skills and passions.  You decide where and how you want to develop, and we help get you there with customizable career progression and a comprehensive benefits package to support you along the way.  Alongside our suite of traditional benefits encompassing generous PTO, health coverage, disability insurance, paid family leave and more, we&rsquo;ve launched extended benefits to help meet our employees&rsquo; needs.
  <br/>
  <br/>
 </p>
 <ul>
  <li>
   CapTech is committed to providing a flexible work environment and helping our employees achieve a work-life balance that suits their individual needs. Employees must be available to work onsite in a client location or a CapTech office as requested. We allow CapTech employees to work remotely when compatible with CapTech and client needs.
  </li>
  <li>
   Learning &amp; Development &ndash; Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
  </li>
  <li>
   Modern Health &ndash;A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life&rsquo;s ups and downs
  </li>
  <li>
   Carrot Fertility &ndash;Inclusive fertility and family-forming coverage for all paths to parenthood &ndash; including adoption, surrogacy, fertility treatments, pregnancy, and more &ndash; and opportunities for employer-sponsored funds to help pay for care
  </li>
  <li>
   Fringe &ndash;A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them &ndash; ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
  </li>
  <li>
   Employee Resource Groups &ndash; Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
  </li>
  <li>
   Philanthropic Partnerships &ndash; Opportunities to engage in partnerships and pro-bono projects that support our communities.
  </li>
  <li>
   401(k) Matching &ndash; Generous matching and no vesting period to help you continue to build financial wellness
  </li>
 </ul>
 <p>
  CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness &mdash; each foundational to our core values.  We strive to create a diverse environment where each employee is encouraged to bring their unique ideas, backgrounds and experiences to the workplace. For more information about our Diversity, Inclusion and Belonging efforts, click HERE.  As part of this commitment, CapTech will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Laura Massa directly via email lmassa@captechconsulting.com.
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 </p>
 <p>
  At this time, CapTech cannot transfer nor sponsor a work visa for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship.
 </p>
</div>


Machine Learning / Data Science Engineer

MILAHA

<div><p>Communication
<br>
Internal Communication:
<br>
Internal Business Units
<br>
All Internal Department
<br>
Senior Leadership Team
<br>
Purpose:
<br>
 Innovation in AI Products and Services
<br>
 Customer Experience Enhancement:
<br>
 Data Integration and Democratization
<br>
 Predictive and Prescriptive Analytics
<br>
 Change Management and Adoption of AI
<br>
 Cloud and Scalable AI Infrastructure
<br>
 Data Governance and Ethics
</p><p>External Communication:
<br>
External IT Vendors
<br>
Software Integrators
</p><p>Occupational Health &amp; Safety and Environment
<br>
Accountability:
<br>
Are accountable for their acts and omissions.
<br>
Responsibility:
<br>
To follow agreed safe systems of work; to follow training and instructions; and to report accidents, incidents and near misses.
<br>
Authority:
<br>
To stop work if they think the work is unsafe.</p></div>
<br><div><div>Education &amp; Professional Qualification:
<br>
Bachelor&rsquo;s Degree in Computer Science, Data Science
<br>
Artificial Intelligence, Statistics, Mathematics, Engineering, Information Technology
<br>
Master&rsquo;s Degree (preferred):
<br>
Data Science, Artificial Intelligence or Machine Learning, Computer Science, Business Analytics, Statistics or Applied Mathematics, Operations Research
<br>
Professional Experience:
<br>
<ul><li>8 years of hands-on experience in data science, machine learning, or AI roles, including developing and deploying AI models and algorithms.
</li><li>Experience with machine learning techniques, such as:
</li><li>Supervised/Unsupervised Learning
</li><li>Deep Learning (e.g., Neural Networks, CNNs, RNNs)
</li><li>Natural Language Processing (NLP)
</li><li>Computer Vision
</li></ul>Geographic Experience:
<br>
A plus
<br>
Computer Skills:
<br>
data science, machine learning, AI, including developing and deploying AI models and algorithms
<br>
Language Skills:
<br>
Business fluent English
<br>
Arabic Language is an advantage.</div></div>
<br><div><div>Strategic Leadership &amp; Vision
<br>
<ul><li>Define and execute the organization&rsquo;s Data Science &amp; AI strategy in alignment with business goals.
</li><li>Identify and prioritize opportunities where AI and data driven solutions enhance efficiency, customer experience, product offerings, and revenue generation.
</li><li>Lead the design of a unified data and AI architecture, including the development of a scalable Data Lakehouse, semantic layers, feature stores, and streaming/batch data integration.
</li><li>Drive the Generative AI roadmap&mdash;selecting LLM providers, designing RAG architectures, and enabling enterprise wide AI capabilities.
</li><li>Oversee FinOps practices to optimize cloud and compute costs associated with AI, GPU workloads, and large scale data storage.
</li></ul>AI &amp; Data Engineering Execution
<br>
<ul><li>Oversee the end to end development, validation, deployment, and lifecycle management of machine learning and AI models.
</li><li>Implement CI/CD/CT pipelines to ensure automated, continuous, and reliable model updates.
</li><li>Build and maintain vector database infrastructure to support semantic search, contextual AI, and long term knowledge retrieval.
</li><li>Ensure data pipelines, platforms, and architectures are optimized for performance, scalability, and resilience.
</li></ul>Governance, Risk, Compliance &amp; Ethics
<br>
<ul><li>Implement data governance, security, and privacy standards, including RBAC/ABAC and protection of PII and sensitive datasets.
</li><li>Establish and monitor automated controls for model drift, fairness, explainability, and ethical use of AI.
</li><li>Ensure compliance with relevant regulations (e.g., GDPR, HIPAA) and internal policies.
</li><li>Maintain best practices for data quality, versioning, reproducibility, and auditability.
</li></ul>Innovation &amp; Continuous Improvement
<br>
<ul><li>Lead experimentation with new algorithms, methods, and technologies to maintain a cutting edge AI ecosystem.
</li><li>Promote a culture of continuous improvement, refining processes, tools, and models to enhance performance and business impact.
</li></ul>Team Leadership &amp; Capability Building
<br>
<ul><li>Mentor and develop a high performing team of data scientists, AI engineers, and data professionals.
</li><li>Oversee training and upskilling initiatives to ensure the team remains current with emerging technologies and methodologies.
</li></ul>Stakeholder Management &amp; Communication
<br>
<ul><li>Serve as a strategic advisor between business and technical teams&mdash;translating business challenges into AI solutions and articulating AI outcomes clearly to non technical stakeholders.
</li><li>Provide regular updates to leadership on progress, performance metrics, model outcomes, and business results.
</li><li>Drive cross department collaboration to ensure successful adoption and integration of AI solutions.
</li></ul>Technology, Tools &amp; Vendor Management
<br>
<ul><li>Lead the selection, integration, and management of AI platforms, data tools, and vendor partnerships.
</li><li>Manage budgets for data science and AI initiatives, ensuring optimal allocation of resources.
</li><li>Make decisions related to hiring, vendor selection, and solutions procurement that support strategic AI objectives.</li></ul></div></div>
<br><div><div>Education &amp; Professional Qualification:
<br>
Bachelor&rsquo;s Degree in Computer Science, Data Science
<br>
Artificial Intelligence, Statistics, Mathematics, Engineering, Information Technology
<br>
Master&rsquo;s Degree (preferred):
<br>
Data Science, Artificial Intelligence or Machine Learning, Computer Science, Business Analytics, Statistics or Applied Mathematics, Operations Research
<br>
Professional Experience:
<br>
<ul><li>8 years of hands-on experience in data science, machine learning, or AI roles, including developing and deploying AI models and algorithms.
</li><li>Experience with machine learning techniques, such as:
</li><li>Supervised/Unsupervised Learning
</li><li>Deep Learning (e.g., Neural Networks, CNNs, RNNs)
</li><li>Natural Language Processing (NLP)
</li><li>Computer Vision
</li></ul>Geographic Experience:
<br>
A plus
<br>
Computer Skills:
<br>
data science, machine learning, AI, including developing and deploying AI models and algorithms
<br>
Language Skills:
<br>
Business fluent English
<br>
Arabic Language is an advantage.</div></div>

Specialist - AI & Data Architect

Presight

<div>
 <p>
  Senior Data Scientist &ndash; Large Language Models | Abu Dhabi, UAE
 </p>
 <p>
  <br/>
 </p>
 <p>
  Position Overview
 </p>
 <p>
  We are seeking a Senior Data Scientist with strong expertise in large language models (LLMs), agentic workflows, and applied machine learning. This role involves leading the design, training, and deployment of next-generation AI solutions that power intelligent agents, natural language interfaces, and knowledge-driven applications across domains. You will collaborate with cross-functional teams to deliver scalable, high-performance AI systems that unlock value from unstructured and structured data.
 </p>
 <p>
  Key Responsibilities
 </p>
 <ul>
  <li>
   Design, build, and optimize LLM-based solutions for tasks such as text understanding, summarization, semantic search, dialogue systems, and reasoning.
  </li>
  <li>
   Develop and orchestrate agentic workflows, integrating LLMs with tools, APIs, and data pipelines for autonomous task execution.
  </li>
  <li>
   Fine-tune and align LLMs on domain-specific datasets, leveraging techniques such as RLHF, prompt engineering, retrieval-augmented generation (RAG), and knowledge grounding.
  </li>
  <li>
   Architect multi-modal AI pipelines combining LLMs with computer vision, knowledge graphs, and structured data.
  </li>
  <li>
   Ensure scalability, efficiency, and reliability of deployed models on cloud and edge environments.
  </li>
  <li>
   Stay updated with the latest research in GenAI, agents, and applied AI, translating findings into innovative product features.
  </li>
  <li>
   Collaborate with software engineers, data engineers, and product managers to integrate AI models into production systems.
  </li>
  <li>
   Document methodologies, publish internal best practices, and present findings to stakeholders.
  </li>
 </ul>
 <p>
  Requirements
 </p>
 <p>
  Qualifications
 </p>
 <p>
  &bull; Master&rsquo;s or Ph.D. in Computer Science, Data Science, Machine Learning, Applied Mathematics, or related field.
 </p>
 <p>
  &bull; Advanced research and practical experience with large-scale machine learning models.
 </p>
 <p>
  &bull; 5+ years of hands-on experience in AI, machine learning, or intelligent agent system development.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Experience
 </p>
 <p>
  &bull; Proven experience in developing and deploying LLM-powered solutions.
 </p>
 <p>
  &bull; Strong background in natural language processing (NLP), applied machine learning, and GenAI projects.
 </p>
 <p>
  &bull; Experience with orchestration frameworks (LangChain, LlamaIndex, Haystack, or equivalent).
 </p>
 <p>
  Skills
 </p>
 <ul>
  <li>
   Proficiency in Python and ML frameworks (TensorFlow or PyTorch, Hugging Face).
  </li>
  <li>
   Hands-on with LLM fine-tuning, evaluation, and optimization.
  </li>
  <li>
   Knowledge of RAG pipelines, embeddings, and vector databases (e.g., FAISS, Pinecone, Milvus).
  </li>
  <li>
   Familiarity with agentic architectures and workflow automation frameworks.
  </li>
  <li>
   Familiarity with backend frameworks (e.g., FastAPI), containerization (Docker), and databases (PostgreSQL, Redis).
  </li>
  <li>
   Strong analytical, problem-solving, and research skills.
  </li>
  <li>
   Excellent communication skills to explain technical concepts to diverse audiences.
  </li>
  <li>
   Ability to thrive in fast-paced, collaborative environments.
  </li>
 </ul>
 <p>
  Preferred
 </p>
 <ul>
  <li>
   Experience with multi-agent systems, autonomous reasoning, and planning frameworks.
  </li>
  <li>
   Experience with vector databases (FAISS, Pinecone, Milvus) and orchestration frameworks (LangChain, LlamaIndex, Haystack).
  </li>
  <li>
   Knowledge of Model Context Protocol (MCP) and reasoning models is a plus.
  </li>
  <li>
   Familiarity with responsible AI, bias mitigation, and data privacy in LLM systems.
  </li>
  <li>
   Knowledge of real-time applications (e.g., chatbots, copilots, AI agents). Knowledge of AI coding tools (Cursor, Claude code, OpenAI Codex, github copilot
  </li>
 </ul>
</div>


Senior Data Scientist

Michigan State University

<div></div><div><div><div><div><div><ul><li>East Lansing, Michigan, United States
</li> </ul></div><div></div><div><ul><li>Mathematics 10032574
</li> </ul></div><div></div><div><ul><li>Full Time/Part Time: On-Call
</li> </ul></div><div></div><div><ul><li>Support Staff
</li> </ul></div><div></div><div><ul><li>Opening on: Apr 10 2026
</li> <div></div><li>Closing at: Apr 15 2026 - 23:55 EDT
</li> </ul></div><div></div><div><ul><li>00
</li> </ul></div><div></div><div><ul><li>Pay Commensurate with Experience
</li> </ul></div><div></div><div><ul><li>College Of Natural Science
</li> <div></div><li>1121883</li></ul></div></div><div></div><div><div><div><b><br>
</b></div></div><div></div><div><b>
</b></div></div><div><h3 class="jobSectionHeader"><b>Position Summary(Basic Job Function)</b></h3>
<p>
This is a project pay position. Provides professional support. Responsibilities may include general business, science, medical, agricultural or other professional support functions.</p>
<h3 class="jobSectionHeader"><b>
Unit Position Summary</b></h3>
<p>
Responsibilities for this position include:</p>
<p>
Combining topological data analysis and other mathematical methods with machine learning/deep learning algorithms for the predictions of molecular biological properties, drug discovery, single-cell RNA-seq data analysis, and viral studies.</p>
<h3 class="jobSectionHeader"><b>
Desired Qualifications</b></h3>
<p>
Preference will be given to Mathematics majors or graduates with experience in machine learning, data science, and/or python coding.</p>
<h3 class="jobSectionHeader"><b>
Equal Employment Opportunity Statement</b></h3>
<p>
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, citizenship, age, disability or protected veteran status.</p>
<h3 class="jobSectionHeader"><b>
Required Application Materials</b></h3>
<p>
Please submit resume or CV with application.</p>
<h3 class="jobSectionHeader"><b>
Work Hours</b></h3>
<p>
ON-CALL</p>
<h3 class="jobSectionHeader"><b>
Website</b></h3>
<p>
HTTP://MATH.MSU.EDU</p>
<h3 class="jobSectionHeader"><b>
Remote Work Statement</b></h3>
<p>
MSU strives to provide a flexible work environment and this position has been designated as remote-friendly. Remote-friendly means some or all of the duties can be performed remotely as mutually agreed upon.</p></div></div></div></div>

Professional Aide Project Pay

Mindrift

<div>
 <em>
  Please submit your CV in English and indicate your level of English proficiency.
  <br/>
  <br/>
 </em>
 Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.
 <strong>
  Participation is project-based, not permanent employment.
  <br/>
  <br/>
 </strong>
 <strong>
  What This Opportunity Involves
  <br/>
  <br/>
 </strong>
 While each project involves unique tasks, contributors may:
 <br/>
 <br/>
 <ul>
  <li>
   Design original computational STEM problems that simulate real scientific workflows
  </li>
  <li>
   Create problems that require Python programming to solve
  </li>
  <li>
   Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks)
  </li>
  <li>
   Develop problems requiring non-trivial reasoning chains and creative problem-solving approaches
  </li>
  <li>
   Verify solutions using Python with standard libraries (Numpy, Pandas, Scipy, scikit-learn)
  </li>
  <li>
   Document problem statements clearly and provide verified correct answers
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We Look For
  <br/>
  <br/>
 </strong>
 This opportunity is a good fit for ML specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:
 <br/>
 <br/>
 <ul>
  <li>
   5+ years of hands-on machine learning experience with proven business impact
  </li>
  <li>
   Portfolio of completed projects and publications showcasing real-world problem-solving
  </li>
  <li>
   Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels)
  </li>
  <li>
   Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and their practical applications
  </li>
  <li>
   Expert with SQL and database operations for data manipulation and analysis
  </li>
  <li>
   Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases)
  </li>
  <li>
   Understanding of MLOps practices and model deployment workflows
  </li>
  <li>
   Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain)
  </li>
  <li>
   Strong written English (C1+)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  How It Works
  <br/>
  <br/>
 </strong>
 Apply &rarr; Pass qualification(s) &rarr; Join a project &rarr; Complete tasks &rarr; Get paid
 <br/>
 <br/>
 <strong>
  Project time expectations
  <br/>
  <br/>
 </strong>
 For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.
 <br/>
 <br/>
 <strong>
  Compensation
  <br/>
  <br/>
 </strong>
 On this project, contributors can earn up to
 <strong>
  $90 per hour equivalent
 </strong>
 , depending on their level and pace of contribution.
 <br/>
 <br/>
 Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.
</div>


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