Pre-screened and vetted.
Mid-level Data Analyst/Data Engineer specializing in machine learning and NLP
Mid-level Data Scientist specializing in ML, NLP, and LLM-powered analytics
Senior Product Manager specializing in B2B SaaS platforms and AI/ML features
Senior CRM and customer operations professional specializing in e-commerce lifecycle marketing
“CRM/lifecycle marketer from Lancer Skincare with hands-on ownership of high-volume promotional campaigns, especially complex subscription and discount scenarios. Stands out for combining rigorous QA, real-time issue management, and post-campaign analysis to improve both revenue outcomes and customer experience.”
Director-level business development leader specializing in retail and restaurant growth
“Multi-unit operator and sales leader with experience running 21 restaurants across central and south Texas, owning operations end to end and delivering revenue growth, year-over-year sales gains, and top retention results. Also demonstrated entrepreneurial customer growth by expanding a wine client base from 100 to 500 through referrals, events, and a monthly shipment program while keeping acquisition costs low.”
Junior GTM and product marketing analyst specializing in AI communications
“Early-career candidate with hands-on B2B SaaS and GTM exposure through a Cloudera internship, where they led a multi-vendor evaluation process and influenced the final software selection. They pair analytical research and dashboarding with strong external communication, and also drove campus partnerships and a 30% social engagement lift as a Princeton Review ambassador.”
Mid-level Full-Stack Software Engineer specializing in backend and AI systems
“Full-stack and AI engineer who has built both user-facing products and production LLM systems, including an AI log-classification and incident-triage platform that cut manual triage by 60%+ and improved routing accuracy by 35%. Also brings cross-functional systems experience from an AI-driven digital twin project spanning HPC, Unity, AR, and large-scale simulation visualization.”
Mid-level Machine Learning Engineer specializing in healthcare and enterprise analytics
Executive Sales Leader specializing in Enterprise SaaS GTM and global revenue growth
“Revenue/sales operations and GTM builder for early-stage startups who designs repeatable sales processes (CRM pipeline stages, MEDDPICC, Challenger Sales) and operating cadences (OKRs) to improve conversion and forecasting. Also mentors product/technical founders—e.g., through the Canadian Technology Accelerator—helping a fintech founder establish segmentation, metrics, and an outbound motion that produced early recurring revenue and investor readiness.”
Mid-level GenAI Engineer specializing in RAG systems and AI agents
“LLM/agentic systems builder who has deployed production solutions for a resource management firm, using an MCP-driven architecture with Neo4j + Elasticsearch and a ChatGPT frontend to generate candidate/company “SmartPacks” and answer entity Q&A. Also built a LangGraph/LangSmith-orchestrated multi-agent workflow that automates data-infra change requests end-to-end (impact analysis, SQL + tests, and PR creation), and delivered a ~60% latency reduction through TTL-based context caching while improving accuracy via a business data dictionary.”
Director-level Enterprise Customer Success leader specializing in Healthcare SaaS
Intern Robotics Software Engineer specializing in ROS2 autonomy and LiDAR localization
“Robotics software engineer focused on production-grade autonomous mobile robot (AMR) navigation in warehouse-style environments, with deep hands-on ROS2/ROS Noetic experience across SLAM, AMCL/NDT LiDAR localization, and Nav2 integration. Strong in real-time debugging and performance tuning using rosbag-driven regression workflows, plus containerized deployment (Docker/Compose) and distributed robot/edge-device communication via MQTT/REST.”
Mid-level AI/ML Engineer specializing in predictive modeling, NLP, and recommender systems
“AI/ML manager who has deployed production NLP in healthcare—mining unstructured clinical notes and combining them with structured patient data to predict readmissions, with strong emphasis on data alignment and terminology normalization. Also experienced operationalizing ML with Airflow/MLflow and AWS Step Functions/SageMaker, plus stakeholder-facing Power BI dashboards (e.g., marketing customer segmentation).”
Mid-level Marketing Analytics & Growth Specialist in performance marketing
“Paid media specialist with nonprofit/fundraising experience at Keelworks Foundation, running high-spend acquisition across Google, Meta, and LinkedIn (and familiar with TikTok). Uses CRM-driven funnel segmentation and disciplined A/B testing across ads, landing pages, and email flows; has recovered stalled performance and delivered ~10% donation growth while tracking deep donor-quality KPIs (lead-to-donor, retention, avg gift).”
Junior sales and operations professional with experience in retail, education, and healthcare
“Candidate brings hands-on grassroots marketing and operations experience from a breakdance nonprofit, where they drove outreach to sponsors, venues, staff, and high-profile community figures to execute events. They also supported a coffee shop CEO with local market research, AI-assisted analysis, and college-focused customer targeting, showing a blend of creative community engagement and practical go-to-market thinking.”
Junior AI/ML Engineer specializing in healthcare and financial risk modeling
“Built and productionized a clinical NLP + patient risk stratification platform at Dermanture, combining Spark/PySpark pipelines with BERT/BioBERT for entity extraction and text classification and downstream risk models in TensorFlow/scikit-learn. Experienced running regulated, auditable ML workflows with Airflow and AWS SageMaker, emphasizing data validation (Great Expectations), drift monitoring, and explainability (SHAP) to drive clinician trust and adoption.”
Mid-level GenAI/Data Engineer specializing in LLMs, RAG systems, and fraud detection
“ML/NLP engineer with banking domain experience who built a GenAI-powered fraud detection and risk intelligence system at Origin Bank, combining RAG (LangChain + FAISS), fine-tuned BERT NER, and GPT-4/Sentence-BERT embeddings. Delivered measurable impact (25% higher fraud detection accuracy, 40% less manual review) and emphasizes production-grade pipelines on AWS SageMaker/Airflow with strong data validation and scalable PySpark processing.”
“At Liberty Mutual, built a production underwriting decision assistant combining LLM reasoning with quantitative models and strong auditability. Implemented a claims-based response verification pipeline that cut hallucinations from 18% to 3% and materially improved user trust/validation scores. Experienced orchestrating ML/LLM workflows end-to-end with Airflow, Kubeflow Pipelines, and Jenkins, including SLA-focused pipeline hardening.”
Mid-level Machine Learning & AI Engineer specializing in Generative AI, NLP, and MLOps
“Built and deployed production LLM systems for summarizing sensitive legal and financial documents, emphasizing GDPR-aligned privacy controls and scalable hybrid cloud architecture. Experienced with Kubernetes/Airflow orchestration and rigorous testing/monitoring practices, and has delivered measurable business impact (18% conversion lift) by translating AI outputs for non-technical marketing stakeholders.”
Director of Growth Marketing specializing in multi-channel acquisition and attribution
“Growth and partnerships leader spanning creator ecosystem and B2B SaaS GTM. Drove measurable revenue outcomes by combining performance-based creator deals (including whitelisting/retargeting and geo lift testing) with a repeatable demand engine using Google Search, LinkedIn ABM, AI-personalized outbound, and HubSpot automation—scaling MRR from $15K to $110K and lifting trial-to-paid conversion from ~3.4% to ~9% via persona-based onboarding.”
“Built and deployed a production AI customer support chatbot at Unique Design Inc. using FastAPI, AWS, Docker, and retrieval-based grounding on internal documents. Stands out for hands-on ownership across discovery, deployment, incident debugging, and post-launch iteration, with a strong focus on making LLM systems reliable and safe in real business workflows.”