ml engineer

Interon IT Solutions

<div>
 <strong>
  Job Title:
 </strong>
 AI/ML Engineer (Python, AWS, GenAI)
 <br/>
 <br/>
 <strong>
  Location:
 </strong>
 Reston, VA (In-person interviews required)
 <br/>
 <br/>
 <strong>
  Candidate Requirement:
 </strong>
 Local to East Coast only
 <br/>
 <br/>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 Client is seeking an AI/ML Engineer to design and deliver end-to-end AI/ML and Generative AI solutions in a cloud-native AWS environment. The ideal candidate will have strong Python engineering skills, experience deploying ML/GenAI workloads on AWS, and hands-on expertise building RAG pipelines and MLOps workflows.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and implement end-to-end AI/ML and Generative AI solutions using Python, including training, evaluation, optimization, and deployment.
  </li>
  <li>
   Build and maintain cloud-native applications on AWS using Lambda, ECS/Fargate, S3, API Gateway, DynamoDB, RDS/Aurora, SageMaker, and Bedrock.
  </li>
  <li>
   Develop scalable, high-performance Python microservices using FastAPI/Flask for data pipelines, real-time analytics, and model inference.
  </li>
  <li>
   Architect and operationalize RAG pipelines, embeddings, vector databases, and LLM-powered solutions (chatbots, summarization, semantic search, anomaly detection).
  </li>
  <li>
   Implement CI/CD pipelines (GitHub/GitLab/CodePipeline) and Infrastructure-as-Code using Terraform/CloudFormation.
  </li>
  <li>
   Build and support MLOps workflows: model versioning, containerized training/inference, automated retraining, monitoring, and performance tuning.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Skills
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Strong hands-on experience in Python development for AI/ML and GenAI solutions.
  </li>
  <li>
   Proven experience working with AWS services for application and ML deployments.
  </li>
  <li>
   Experience building APIs/microservices using FastAPI or Flask.
  </li>
  <li>
   Hands-on experience with RAG, embeddings, and vector databases.
  </li>
  <li>
   Experience with CI/CD and IaC (Terraform/CloudFormation).
  </li>
  <li>
   Strong understanding of MLOps practices and production model monitoring.
  </li>
 </ul>
</div>


AI/ML Engineer

Microsoft

<div>
 <strong>
  Overview
  <br/>
  <br/>
 </strong>
 You&rsquo;ll help build core generative AI and multimodal capabilities that power customer-facing AI services at global scale. In this role, you&rsquo;ll combine software engineering with applied ML expertise to design, ship, and operate production systems&mdash;using techniques like context engineering, synthetic data generation, and rigorous evaluation/metrics to continuously improve quality. You&rsquo;ll collaborate closely across product, research, and service engineering to deliver secure, performant improvements for enterprise customers.
 <br/>
 <br/>
 This position is in-office, with a minimum of 3 days/week in office.
 <br/>
 <br/>
 Microsoft&rsquo;s mission is to empower every person and every organization on the planet to achieve more, and we&rsquo;re dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders toperform at a high level each day. Join us and help shape the future of the world.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, build, and operate production-grade generative AI and multimodal systems, with ownership from implementation through deployment and live-site operations.
  </li>
  <li>
   Contribute to the design and implementation of core GenAI capabilities (e.g., retrieval-augmented generation, context and memory, orchestration) and make data-driven tradeoffs across quality, latency, cost, and safety.
  </li>
  <li>
   Improve model and system quality using evaluation frameworks, experiment design, and production telemetry; build robust testing, monitoring, and regression coverage.
  </li>
  <li>
   Work with security, privacy, and compliance partners to build solutions that meet enterprise requirements and align with Responsible AI standards and practices.
  </li>
  <li>
   Collaborate with teammates through design reviews, code reviews, and debugging to unblock delivery and improve architecture, code quality, and ML engineering practices.
  </li>
  <li>
   Partner with product and customers to understand scenarios, translate requirements into well-designed APIs and developer experiences, and contribute to adoption through documentation and samples.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 Required Qualifications
 <br/>
 <br/>
 <ul>
  <li>
   Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3+ years of experience in software engineering, machine learning engineering, or applied AI (or equivalent experience).
  </li>
  <li>
   Experience contributing to technical designs and delivering features in complex codebases (e.g., writing design docs, reviewing changes, and improving reliability/performance).
  </li>
  <li>
   Experience building and shipping generative AI systems (including multimodal scenarios).
  </li>
  <li>
   Experience building and operating ML/AI systems in cloud environments; familiarity with MLOps practices (Azure a plus).
  </li>
  <li>
   Experience partnering with cross-functional stakeholders to define requirements and drive technical decisions.
  </li>
  <li>
   Advanced degree in Computer Science, Machine Learning, or related field.
  </li>
  <li>
   Experience with prompt engineering, retrieval-augmented generation (RAG), and memory/agent frameworks.
  </li>
  <li>
   Familiarity with compliance and security standards in enterprise AI solutions.
  </li>
  <li>
   Track record of delivering enterprise-facing AI products at scale.
   <br/>
   <br/>
  </li>
 </ul>
 Other Requirements:
 <br/>
 <br/>
 Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:
 <br/>
 <br/>
 <ul>
  <li>
   Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
   <br/>
   <br/>
  </li>
 </ul>
 Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $131,400 - $215,400 per year.
 <br/>
 <br/>
 Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
 <br/>
 <br/>
 https://careers.microsoft.com/us/en/us-corporate-pay
 <br/>
 <br/>
 This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
 <br/>
 <br/>
 Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about
 <strong>
  requesting accommodations.
 </strong>
</div>


ML Engineer

Techtimize

<p><b>Senior Machine Learning Engineer (Computer Vision &ndash; Object Detection)</b></p><p><b>Job Summary</b></p><p>We are looking for a hands-on <b>Senior ML Engineer (Computer Vision)</b> with deep expertise in <b>object detection</b> and strong production delivery skills.</p><p>You will own end-to-end detection systems &mdash; from dataset design and training pipelines to optimized inference services, monitoring, and continuous improvement in real-world environments.</p><p><b>Key Responsibilities</b></p><ul><li>Design, train, debug, and improve state-of-the-art object detection models</li><li>Build robust training pipelines (datasets, augmentation, caching, versioning, reproducible experiments)</li><li>Conduct systematic error analysis and ablation studies</li><li>Develop advanced detection workflows (multi-stage pipelines, ensembles, custom post-processing)</li><li>Optimize inference for GPU performance (latency, throughput, memory)</li><li>Export and deploy models (ONNX, TorchScript, TensorRT)</li><li>Build production services using Docker, Linux, CI/CD, FastAPI and/or gRPC</li><li>Implement comprehensive testing (unit, integration, regression, golden test sets)</li><li>Set up monitoring systems (logging, metrics dashboards, drift tracking, retraining triggers)</li><li>Translate research papers into working prototypes and production systems</li></ul><p><b>Required Skills &amp; ExperiencePython &amp; ML Engineering</b></p><ul><li>Advanced Python engineering (clean architecture, typing, testing, profiling)</li><li>Strong hands-on experience with <b>PyTorch (mandatory)</b></li><li>TensorFlow (optional)</li><li>Experiment tracking (W&amp;B, MLflow)</li><li>Config management (Hydra/OmegaConf)</li><li>Dataset versioning (DVC or similar)</li></ul><p><b>Computer Vision Fundamentals</b></p><ul><li>Strong CV foundations (geometry, distortions, preprocessing, camera models)</li><li>OpenCV expertise</li><li>Evaluation metrics: mAP, IoU, precision/recall, PR curves</li></ul><p><b>Deep Object Detection</b></p><p>Experience with modern detectors such as:</p><ul><li>YOLO (v5/v8/v9)</li><li>Faster R-CNN</li><li>RetinaNet</li><li>EfficientDet</li><li>DETR variants</li></ul><p>Experience with:</p><ul><li>Multi-stage detection pipelines</li><li>Ensemble strategies</li><li>Domain-optimized post-processing</li></ul><p><b>Production ML &amp; MLOps</b></p><ul><li>ONNX runtime + TorchScript or TensorRT</li><li>GPU optimization &amp; inference tuning</li><li>Docker, Linux, CI/CD (GitHub Actions or GitLab CI)</li><li>FastAPI and/or gRPC deployment</li><li>Monitoring, model versioning, rollback strategies</li></ul><p>Job Type: Fulltime - Onsite<br/>Location: Lahore</p><p>Job Type: Full-time</p><p>Work Location: In person</p>

Senior ML Engineer

Radiance Technologies Inc.

<div><div>Work Location: Office &amp; Onsite at NASIC</div><div></div><div>
Radiance Technologies is seeking an experienced AI/ML Engineer to support the National Air and Space Intelligence Center (NASIC). The selected candidate will design, develop, test, and deliver AI/ML components to advance the Intelligence Community&rsquo;s (IC) ability to characterize complex adversary threats with speed and accuracy. This role involves integrating modernized analytic tools, leveraging relevant data sources, and delivering scalable AI/ML solutions within government cloud architectures.</div><div></div><div>
You will design, integrate, and optimize full-lifecycle ML pipelines, from data ingestion and model training to deployment and monitoring, ensuring all solutions meet DoW and Intelligence Community security and compliance standards.</div><div>
You will evaluate emerging technologies, assessing their ability to achieve long-term, reliability, scalability, and mission success. This role requires ability to integrate advanced AI/ML capabilities within secure environments, and a commitment to delivering solutions that adhere to federal security and compliance standards.</div><div></div><div>
Required Qualifications:</div><ul><li><div>
Bachelor&rsquo;s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.</div></li><li><div>
U.S Citizenship with the ability to obtain and maintain a TS/SCI security clearance.</div></li><li><div>
3 + Years of direct work experience</div></li><li><div>
Proven experience in designing, developing, and deploying AI/ML solutions.</div></li><li><div>
Practical experience with scalable cloud-native applications and event-driven architecture.</div></li><li><div>
Proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.</div></li><li><div>
Experience with Kubernetes-based platforms and CI/CD pipelines.</div></li><li><div>
Experience collaborating with multidisciplinary technical teams and supporting customer-facing technical engagements</div></li></ul><div></div><div>
Key Responsibilities-</div><div></div><div>
Tool Integration:</div><ul><li><div>
Integrate modernized analytic tools into AI/ML capabilities.</div></li><li><div>
Develop user-friendly interfaces for AI/ML tools.</div></li><li><div>
Incorporate monitoring services, including user-enabled monitoring, model drift detection, and model demand tracking.</div></li></ul><div></div><div>
Data Requirements:</div><ul><li><div>
Leverage relevant data sources and types for AI/ML models, including connections to future data sources.</div></li><li><div>
Provide access to datasets necessary for training, testing, and validating AI/ML models.</div></li><li><div>
Document and ensure reproducibility of data preparation steps.</div></li></ul><div></div><div>
AI/ML Services:</div><ul><li><div>
Deliver a scalable AI/ML software stack supporting the AI/ML lifecycle across NASIC.</div></li><li><div>
Ensure AI/ML components operate within the architecture, data pipelines, and security frameworks defined by the government.</div></li><li><div>
Design processes for easy sharing of AI/ML models.</div></li></ul><div></div><div>
AI/ML Models:</div><ul><li><div>
Design scalable, maintainable, shareable, and adaptable AI/ML models.</div></li><li><div>
Train models using government-approved datasets and document training procedures and evaluation results.</div></li><li><div>
Define retraining triggers, update procedures, and versioning practices to ensure ongoing model accuracy and reliability.</div></li><li><div>
Adhere to industry-accepted AI/ML development principles, including transparency, accountability, and responsible use of data and AI/ML.</div></li></ul><div></div><div>
Desired:</div><ul><li><div>
Kubernetes certifications (CKA, CKAD)</div></li><li><div>
Active TS/SCI</div></li></ul><div></div><div>
Radiance Technologies is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.</div></div>

Fintech

<div><p><b>Join Fintech in Tampa, Florida as an AI/ML Engineer!</b></p>
<p>
We are seeking an AI Engineer to design, build, and operate AI solutions that drive measurable business outcomes. Will have to partner with product managers, data engineers, and analysts to convert use cases into production-grade services&mdash;spanning traditional ML, generative AI (LLMs), and intelligent automation&mdash;using modern MLOps practices. Will have to own model lifecycle, scalability, observability, and security-by-design to ensure responsible, reliable AI in production.</p>
<p><b>
Essential Functions:</b></p>
<p>
Project Responsibility: End-to-end AI solutions.</p>
<p><b>
Technical Competencies:</b></p>
<p><b>
Data Analysis</b></p>
<ul>
<li>Extensive experience in data analysis using Python.</li>
</ul>
<p><b>Machine Learning &amp; Deep Learning</b></p>
<ul>
<li>Proficient with classical ML models and deep learning frameworks (PyTorch/TensorFlow)</li>
<li>Strong grasp of model evaluation, optimization, and training best practices</li>
</ul>
<p><b>Generative AI &amp; LLMs</b></p>
<ul>
<li>Experience with LLMs, embeddings, prompt engineering, and RAG</li>
<li>Familiarity with fine‑tuning (LoRA/QLoRA) and applying guardrails/safety filters</li>
</ul>
<p><b>MLOps / GenAIOps</b></p>
<ul>
<li>CI/CD pipelines for ML/LLM, model registry, automated deployments</li>
<li>Monitoring for drift, performance, hallucination rate, and service reliability</li>
</ul>
<p><b>Cloud &amp; Infrastructure</b></p>
<ul>
<li>Hands‑on with cloud ML platforms preferably Azure</li>
<li>Strong understanding of containerization (Docker) and IaC (Terraform/Bicep)</li>
</ul>
<p><b>Data Platform</b></p>
<ul>
<li>Familiarity with Moderns data platform like Vector DB/Graph Databases</li>
<li>Familiarity with different AI Architecture layers</li>
<li>Implementing data quality checks, lineage, and observability</li>
</ul>
<p><b>Observability &amp; Reliability</b></p>
<ul>
<li>Setting up logs, metrics, dashboards (App Insights, Prometheus/Grafana)</li>
</ul>
<p><b>Responsible AI &amp; Security</b></p>
<ul>
<li>Applying model cards, risk assessments, bias &amp; safety evaluations</li>
<li>Implementing RBAC, secret management, network isolation</li>
</ul>
<p><b>Soft Skills:</b></p>
<ul>
<li>Cross-functional collaboration with product and engineering teams</li>
<li>Technical mentoring for junior engineers</li>
<li>Analytical thinking for complex data problems</li>
<li>Process improvement and efficiency focus</li>
<li>Evaluates vendor tools for specific data use cases</li>
<li>Provides technical feedback on vendor product roadmaps</li>
<li>Problem‑solving mindset &ndash; ability to break down ambiguous business problems into actionable AI/ML solutions</li>
<li>Communication clarity &ndash; explains complex technical concepts in simple, actionable terms to non‑technical stakeholders</li>
<li>Adaptability &amp; learning agility &ndash; stays current with fast‑evolving AI/LLM technologies and adjusts approaches quickly</li>
<li>Critical thinking &ndash; evaluates risks, tradeoffs, and ethical considerations objectively</li>
<li>Product orientation &ndash; focuses on business impact, user experience, and measurable value</li>
</ul>
<p><b>Qualifications:</b></p>
<ul>
<li>Bachelor&rsquo;s/Master&rsquo;s in Computer Science, Data Engineering, Statistics, or related field.</li>
<li>1+ years&rsquo; experience in AI implementation and 3+ years of ML experience.</li>
</ul>
<p><b>Our Benefits:</b></p>
<ul>
<li>Employer Matched 401K</li>
<li>Company Paid Medical Insurance Option for Employee and Dependent Children</li>
<li>Company Paid Dental Insurance for Employee</li>
<li>Company Paid Vision Insurance for Employee</li>
<li>Company Paid Long and Short-Term Disability</li>
<li>Company Paid Life and AD&amp;D Insurance</li>
<li>18 Paid Vacation Days a Year</li>
<li>Six Paid Holidays</li>
<li>Employee Recognition Programs</li>
<li>Incentive Compensation</li>
<li>Community Outreach Opportunities</li>
<li>Business Casual Dress Code</li>
</ul>
<p><b>About Fintech:</b></p>
<p><i>
For over 35 years, Fintech LLC has redefined how over 1.1 million B2B relationships buy and sell goods and services in the retail, hospitality, and alcohol industries. This integrated platform centralizes invoice data and payments, POS and delivery data, product and cost compliance, price book management, and industry market data using AI, seamless integration capabilities, and proprietary automation technology.</i></p>
<p><i>
Fintech is a Drug-Free Workplace. Fintech is an Equal Opportunity Employer that does not discriminate on the basis of actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth and pregnancy-related conditions), gender identity or expression (including transgender status), sexual orientation, marital status, military service and veteran status, physical or mental disability, genetic information, or any other characteristic protected by applicable federal, state, or local laws and ordinances. Fintech&rsquo;s management team is dedicated to this policy with respect to recruitment, hiring, placement, promotion, transfer, training, compensation, benefits, employee activities, access to facilities and programs and general treatment during employment. We E-Verify.</i></p></div>

Realign

<div>San Francisco, California 94016 Posted March 12th, 2026
 <div></div><p>Looking for more job opportunities? Click here!</p></div>
<br><div><p>Job Type: Contract</p>
<p>Job Category: IT</p>
<p>Job Description</p>
<p></p><p><b>Role: Sr. AI/ML Engineer</b></p><ul><li> <b>Experience</b> &ndash; 10+ Years</li><li> <b>Location</b> - San Francisco, CA &ndash; LOCALS Only</li></ul><div><b>
Required Qualifications</b><br>
<ul><li>Deep expertise in Machine Learning, Generative AI, LLMs, RAG, and AI orchestration.</li><li>Strong understanding of Azure OpenAI, AWS Bedrock, or similar platforms.</li><li>Experience deploying AI in regulated environments.</li><li>Hands-on architectural and engineering leadership capabilities.</li><li>Strong communication skills with VP/Senior Director stakeholders.</li></ul>
 Preferred Qualifications<br>
<ul><li>12+ years in AI/ML, data engineering, or digital transformation.</li><li>Prior experience leading enterprise AI programs.</li><li>Utility domain experience (wildfire, grid, operations).</li><li>Knowledge of Responsible AI frameworks (NIST AI RMF, ISO 42001).</li></ul><br>
<b>
Roles &amp; Responsibilities</b><br>
<b>Role Overview</b><br>
Utilities are accelerating their enterprise AI adoption across Operations, Customer Experience, Wildfire Safety, Regulatory, and IT. The AI Lead will serve as the strategic driver for enterprise AI transformation&mdash;defining vision, governance, enterprise architecture, and leading delivery of high-impact GenAI and ML solutions.</div><div><b><br>
Key Responsibilities</b><br>
<ul><li>Define the enterprise AI vision, roadmap, and operating model.</li><li>Identify and prioritize AI/ML/GenAI opportunities across business units.</li><li>Drive design and deployment of AI solutions including consultation agents, hazard detection, regulatory Q&amp;A automation, and contact center assistants.</li><li>Establish AI governance, compliance, model risk management, and auditability frameworks.</li><li>Lead cross-functional AI programs spanning IT, Operations, Customer Care, Regulatory, Safety, and Field Ops.</li><li>Mentor and guide data scientists, ML engineers, architects, and product owners.</li><li>Promote AI literacy, change management, and best practices across the enterprise.</li></ul></div><p></p>
<p>Required Skills</p>
<p>DEVOPS ENGINEER</p> <p>SENIOR EMAIL SECURITY ENGINEER</p></div>

Sr. AI/ML Engineer-6

ASTIVA HEALTH INC

<p>Description:<br/></p><p>About Us:<br/></p><p>Astiva Health, Inc., located in Orange, CA is a premier health plan provider specializing in Medicare and HMO services. With a focus on delivering comprehensive care tailored to the needs of our diverse community, we prioritize accessibility, affordability, and quality in all aspects of our services. Join us in our mission to transform healthcare delivery and make a meaningful difference in the lives of our members.<br/></p><p>SUMMARY:<br/></p><p>We are seeking a skilled and adaptable AI/ML Engineer to join our fast-moving team building impactful AI solutions in healthcare. Our work focuses on extracting and interpreting data from unstructured medical documents, improving clinical coding accuracy, streamlining administrative processes, and enhancing patient outreach.<br/></p><p>Projects will evolve rapidly, from fine-tuning large language models (LLMs) on specialized medical PDFs, to optimizing OCR pipelines in Azure, and new challenges emerge regularly. This role suits someone who thrives in ambiguity, enjoys hands-on model development, and wants to directly influence healthcare delivery through applied AI/ML.<br/></p><p>ESSENTIAL DUTIES AND RESPONSIBILITIES include the following:<br/></p><p>Design, fine-tune, and optimize large language models (LLMs) and multimodal models for healthcare-specific NLP tasks, such as information extraction, classification, and summarization from clinical documents (e.g., medical charts, patient files, scanned forms).<br/>Develop and improve document understanding pipelines, including fine-tuning OCR / layout-aware models (especially in cloud environments like Azure AI, Azure Foundry) to handle real-world variability in medical forms, handwriting, and scanned PDFs.<br/>Build and iterate on end-to-end ML solutions that transform unstructured healthcare data into structured, actionable insights<br/>Collaborate closely with clinicians, product managers, data annotators, and engineers to define problems, curate/annotate datasets, evaluate model performance against clinical and business metrics, and iterate quickly.<br/>Deploy models into production environments (cloud-based inference, batch processing, or API endpoints) with attention to latency, cost, scalability, and healthcare compliance considerations (HIPAA, data privacy).<br/>Stay current with advancements in LLMs, vision-language models, efficient fine-tuning techniques (LoRA/QLoRA, PEFT), RAG, multimodal AI, and domain-specific healthcare AI research.<br/>Contribute to a culture of rapid prototyping, rigorous evaluation, and continuous improvement in a dynamic project landscape where priorities can shift based on new opportunities or stakeholder needs.<br/>Other duties as assigned<br/></p><p>OTHER SKILLS and ABILITIES:<br/></p><p>Hands-on experience with Azure AI services, Azure Machine Learning, OpenAI on Azure, and Microsoft Foundry<br/>Experience with clinical NLP libraries (scispaCy, medspaCy, cTAKES)<br/>Familiarity with RAG architectures for grounding model decisions<br/>Experience with weak supervision or noisy-label learning<br/>Knowledge of temporal reasoning or longitudinal modeling<br/>Exposure to knowledge graphs or ontology-driven systems<br/>Familiarity with healthcare vocabularies and ontologies:<br/>ICD-10<br/>SNOMED CT<br/>RxNorm (or similar)<br/>Understanding of clinical documentation structure (HPI, Assessment &amp; Plan, medications, etc.<br/></p><p>EXPERIENCE<br/></p><p>Bachelor&rsquo;s Degree in related field<br/>2-4+ years of experience in software engineering, machine learning, or applied NLP<br/>Demonstrated experience taking ML systems from prototype to production<br/>Experience collaborating with non-technical domain experts (e.g., medical coders, clinicians)<br/></p><p>BENEFITS:<br/></p><p>401(k)<br/>Dental Insurance<br/>Health Insurance<br/>Life Insurance<br/>Vision Insurance<br/>Paid Time Off<br/>Free catered lunches<br/>Requirements:<br/></p><p>REQUIRED TECHNICAL SKILLS:<br/></p><p>Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, or equivalent)<br/>Hands-on experience with NLP applied to unstructured text<br/>Experience working with LLMs, including:<br/>Prompting strategies<br/>Fine-tuning for classification or extraction tasks<br/>Model evaluation and error analysis<br/>Experience designing or consuming annotation pipelines and labeled datasets<br/>Familiarity with structured prediction problems (multi-label classification, ranking, or probabilistic inference)<br/>Ability to reason about and mitigate model bias, label noise, and false positives<br/>Strong understanding of production ML systems (versioning, monitoring, iteration)<br/>Experience working with sensitive or regulated data (e.g., HIPAA-covered healthcare data), including privacy-aware data handling and secure ML workflows<br/></p>

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