Centific

Role Description We are looking for entry level Data Scientists/Applied Scientists (through student worker program) with strong Python coding skills, passion for AI quality, the ability to learn, and hands-on experience in delivering exceptional AI experiences, which our customers have come to expect. - Keeping a keen eye on the latest developments in the broad AI community. - Working with science, engineering, and program management teams to integrate the latest large language models (LLMs) such as OpenAI models and open-source models into production systems. - Collaborating with other researchers, data scientists, product managers, and engineers in the team to build tools and improve the end-to-end AI Quality of our production systems. - Leveraging data from various sources and domains to design and implement innovative solutions that achieve rigorous metrics and address customer needs. - Effectively communicating and demonstrating work to stakeholders. Qualifications - Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ years related experience (e.g., statistics predictive analytics, research) - OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ years related experience (e.g., statistics, predictive analytics, research) - OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) - 3+ years’ experience coding in Python and experience in natural language processing or deep learning. - 1+ years' experience in a deep learning library, such as PyTorch or TensorFlow. Requirements - Rate: $40 Per Hour. Company Description Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers.

Role Description Licensed Practical Nurses (LPNs) or Licensed Vocational Nurses (LVNs) are needed for a remote position in the USA. Qualifications - Valid LPN/LVN certification - Strong written communication skills in English (en-US locale) - Comfortable working in a digital environment - Proficiency in Microsoft Office tools: Word, Excel, Outlook - Strong attention to detail and ability to follow complex guidelines - Prior experience with medical data annotation or EMR systems is a plus Requirements - Rate: $32 per hour Company Description Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers.

• Responsible for approving and implementing the changes/updates in projects. • Act as the point of contact between PMs and Senior Program Managers. • Regularly meet with the client to fully understand the client's project requirements. • Work with the Senior Program Manager to build project teams, using the best fit people for the job. • Usually oversees a single project. • Sets methods of daily production reporting. Reviews important data. • Responsible for compiling timekeeping records for management level, approval, and submission. • Helps to drive Lean implementation amongst team members. • Conducts interviews for PM level positions. • Meets with clients for updates on ongoing projects. • Addresses project issues on a process level. • Work with PMs and SPMs to ensure appropriate coverage of all duties within the appropriate process flow. • Initiate changes/updates to the process in a timely manner and ensure they are passed down and implemented by other team members. • Collect and initiate process improvements, eliminating areas of waste to enhance process flow and promote efficiency while passing these on to below team members. • Review End of Day (EOD) reporting pertaining to process flow on assigned projects. • Meet or exceed all daily, weekly, and monthly KPIs pertaining to the specific process flow of the Senior Program Manager. • Additional duties as required.

Role Description Are you pushing the frontier of computer vision, multimodal large models, and embodied/physical AI—and have the publications to show it? Join us to translate cutting-edge research into production systems that perceive, reason, and act in the real world. We are building state-of-the-art Vision AI across 2D/3D perception, egocentric/360° understanding, and multimodal reasoning. As an AI Research Engineer, you will own high-leverage experiments from paper → prototype → deployable module in our platform. We are seeking passionate Engineers to join our cutting-edge labs, you could be part of: - Computer Vision team: Dive into the world of 3D reconstruction, scene understanding, and visual AI. Explore innovative techniques like those used to transform real-world spaces into immersive 3D models. - Physical AI Robotics team: Work at the intersection of simulation, robotics, and AI. Leverage NVIDIA’s Omniverse for advanced 3D simulation and collaboration. What You’ll Do: - Advance Visual Perception: Build and fine-tune models for detection, tracking, segmentation (2D/3D), pose & activity recognition, and scene understanding (incl. 360° and multi-view). - Multimodal Reasoning with VLMs: Train/evaluate vision-language models (VLMs) for grounding, dense captioning, temporal QA, and tool use. - Physical AI & Embodiment: Prototype perception-in-the-loop policies that close the gap from pixels to actions. - Data & Evaluation at Scale: Curate datasets, author high-signal evaluation protocols/KPIs, and run ablations. - Systems & Deployment: Package research into reliable services on a modern stack (Kubernetes, Docker, Ray, FastAPI). - Agentic Workflows: Orchestrate multi-agent pipelines that combine perception, reasoning, simulation, and code generation. Example Problems You Might Tackle: - Long horizon video understanding from egocentric or 360° video. - 3D scene grounding: linking language queries to objects, affordances, and trajectories. - Fast, privacy-preserving perception for on-device or edge inference. - Robust multi-modal evaluation: temporal consistency, open-set detection, uncertainty. - Vision conditioned-policy evaluation in simulation with sim2real stress tests. Qualifications - Masters/Ph.D in CS/EE/Robotics (or related), actively publishing in CV/ML/Robotics. - Strong PyTorch (or JAX) and Python; comfort with CUDA profiling and mixed precision training. - Demonstrated research in computer vision and at least one of: VLMs, embodied/physical AI, 3D perception. - Proven ability to move from paper → code → ablation → result with rigorous experiment tracking. Requirements - Experience with video models (e.g., TimeSFormer/MViT/VideoMAE), diffusion or 3D GS/NeRF pipelines, or SLAM/scene reconstruction. - Prior work on multimodal grounding or temporal reasoning. - Familiarity with ROS2, DeepStream/TAO, or edge inference optimizations. - Scalable training: Ray, distributed data loaders, sharded checkpoints. - Strong software craft: testing, linting, profiling, containers, and reproducibility. - Public code artifacts (GitHub) and first-author publications or strong open source impact. Benefits - Real impact: Your research ships—powering core features in our MVPs and products. - Mentorship: Work closely with our Principal Architect and senior engineers/researchers. - Velocity + Rigor: We balance top-tier research practices with pragmatic product focus. - Salary: $140K - $150K

• Install the operating systems for new mounted servers • Responsible for reinstalling the server operation systems, solving the abnormalities. • Responsible for the daily server maintenance, troubleshooting, repair and follow-up break-fix of the server and other hardware. • Maintain data on internal systems including asset management, ticketing, rack related data • Work with remote vendors/manufacturers or other teams to solve server batch failures and problems • Oncall on duty, responsible for dealing with the problems raised by the business owner side • Collect and check online assets status or issues • Erase drives or other configurations for retiring or relocating servers. • Retrofit some tools by updating or writing scripts • Submit and track the part RMA or media destruction process if needed • Server network troubleshooting • Server lifecycle management including managing the performance of OxMs • Other server operation related work

Role Description We are seeking a highly motivated PhD intern to join Centific’s Vision AI team for a 3–6 month engagement. This is an applied research role for doctoral candidates who want to move beyond the lab and deploy their expertise directly into a live AI operations program. You will be embedded in a production computer vision system processing real-time video feeds across multiple active detection workflows. You will work alongside senior engineers and ML leads to implement, optimize, and measure AI improvement strategies that ship to production on a daily pipeline cadence. The emphasis is on building and shipping: translating model research into working, measurable systems that improve real-world detection performance. Key Responsibilities - Monitor daily pipeline KPIs. - Contribute to post-run analysis. - Document implementation decisions in the team ops ledger. - Assigned to two of the following five focus tracks for the duration of the engagement: - Track 1 — NVIDIA VSS / DeepStream Optimization: Optimize real-time RTSP feed processing and multi-stream batching; configure and tune object tracking to eliminate re-detection false positives and reduce hallucination rates across active surveillance workflows. - Track 2 — Teacher → Student Distillation: Implement and run distillation cycles that compress 20+ epoch full retrains into 3-epoch student passes; maintain and improve three student model variants with daily pipeline integration and performance validation. - Track 3 — SEAL Drift Detection & Auto-Correction: Monitor metrics against a rolling baseline to detect distribution shift; execute targeted fine-tuning or short retraining cycles when drift thresholds are crossed, and systematically reduce recurring false positives. - Track 4 — Self-Distillation & Confidence Calibration: Run self-distillation refinement passes where student models act as their own teachers; apply consistency confidence calibration to narrow confidence intervals, and reduce overconfidence-driven hallucinations. - Track 5 — Student ↔ Student Weighted Peer Learning: Run confidence-weighted ensemble computations across three student model variants, monitor inter-student disagreement rates, route high-disagreement frames to the human review queue, and conduct weekly contribution audits to ensure balanced peer learning and prevent teacher-bias propagation. Qualifications - Currently enrolled in a PhD program in Computer Science, Electrical Engineering, Applied Mathematics, or a closely related field, with a strong orientation toward applied systems and implementation. - Deep expertise in computer vision fundamentals: convolutional neural networks, transformers (ViT, DETR), and generative models. - Strong proficiency in Python and deep learning frameworks including PyTorch and/or TensorFlow. - Hands-on experience with large-scale dataset processing, annotation workflows, or benchmark construction. - Solid understanding of model training techniques: transfer learning, self-supervised learning, and fine-tuning strategies. - Strong implementation skills: ability to take a model research concept and produce a working, measurable system quickly; comfort operating in a daily-cadence production pipeline environment. - Clear written and verbal communication skills; ability to document implementation decisions, pipeline changes, and performance results for both technical and operational audiences. Preferred Qualifications - Hands-on experience with NVIDIA DeepStream, TensorRT, or TAO Toolkit; familiarity with RTSP stream processing, multi-stream batching, or edge inference optimization. - Familiarity with 3D vision, point cloud processing, or LiDAR-visual fusion (particularly in outdoor surveillance or autonomous systems contexts). - Practical experience with knowledge distillation (Teacher → Student, self-distillation, or peer learning), confidence calibration techniques (temperature scaling, isotonic regression, ECE measurement), or active learning / distribution shift detection. - Prior industry internship experience in AI/ML research or data-centric AI. - Prior experience contributing to a production AI pipeline or daily model training cadence; comfort reading and interpreting confusion matrices, F1/Precision/Recall trends, and confidence interval dashboards as operational signals. - Experience with MLOps tools (Weights & Biases, MLflow, DVC) and cloud platforms (AWS, GCP, or Azure). What You Will Gain - Hands-on ownership of a live, production AI system processing real-world surveillance data daily — with measurable KPI targets, real drift events, and deployment decisions that matter. - Mentorship from senior ML engineers and AI leads with deep expertise in deployed Vision AI systems, model distillation, drift correction, and edge inference optimization. - Direct contribution to measurable performance improvements — reductions in hallucination rate, narrowing of confidence intervals, and F1 score gains — on a live public safety AI program. - Access to proprietary datasets, annotation infrastructure, and compute resources for research experiments. - Attribution and credit in Centific’s IP Vault for implemented strategies and methodology contributions, with potential for technical blog posts, internal white papers, or co-authorship on applied research artifacts arising from the program. - Consideration for full-time opportunities upon PhD completion based on performance. Compensation & Logistics - Compensation: Competitive hourly stipend commensurate with PhD program year and experience. - Location: Remote-first; hybrid options available at select office locations. - Start Date: Flexible — rolling admissions, positions filled as qualified candidates are identified. - Duration: 3–6 months, with possibility of extension. - Equipment: Laptop and cloud compute credits provided. - Rate: $50 per hr. Centific is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, citizenship status, age, mental or physical disability, medical condition, sex (including pregnancy), gender identity or expression, sexual orientation, marital status, familial status, veteran status, or any other characteristic protected by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.

Role Description Centific AI Research seeks a PhD Research Intern to design and evaluate speech‑first models, with a focus on Spoken Language Models (SLMs) that reason over audio and interact conversationally. You’ll move ideas from prototype to practical demos, working with scientists and engineers to deliver measurable impact. Scope of Work - End‑to‑end speech dialogue systems (speech‑in/speech‑out) and speech‑aware LLMs. - Alignment between speech encoders and text backbones via lightweight adapters. - Efficient speech tokenization and temporal compression suitable for long‑form audio. - Reliable evaluation across recognition, understanding, and generation tasks—including robustness and safety. - Latency‑aware inference for streaming and real‑time user experiences. Example Projects - Prototype a conversational SLM using an SSL speech encoder and a compact adapter on an existing LLM; compare against strong baselines. - Create a data recipe that blends conversational speech with instruction‑following corpora; run targeted ablations and report findings. - Build an evaluation harness that covers ASR/ST/SLU and speech QA, including streaming metrics (latency, stability, endpointing). - Ship a minimal demo with streaming inference and logging; document setup, metrics, and reliability checks. - Author a crisp internal write‑up: goals, design choices, results, and next steps for productionization. Qualifications - PhD candidate in CS/EE (or related) with research in speech, audio ML, or multimodal LMs. - Fluency in Python and PyTorch, with hands‑on GPU training; familiarity with torchaudio or librosa. - Working knowledge of modern sequence models (Transformers or SSMs) and training best practices. - Depth in at least one area: (a) discrete speech tokens/temporal compression, (b) modality alignment to LLMs via adapters, or (c) post‑training/instruction tuning for speech tasks. - Strong experimentation habits: clean code, ablations, reproducibility, and clear reporting. Preferred Qualifications - Experience with speech generation (neural codecs/vocoders) or hybrid text+speech decoding. - Background in multilingual or code‑switching speech and domain adaptation. - Hands‑on work evaluating safety, bias, hallucination, or spoofing risks in speech systems. - Distributed training/serving (FSDP/DeepSpeed), and experience with ESPnet, SpeechBrain, or NVIDIA NeMo. Tech Stack - PyTorch, CUDA, torchaudio/librosa; experiment tracking (e.g., Weights & Biases). - LLM backbones with lightweight adapters; neural audio codecs and vocoders as needed. - FastAPI/gRPC for services; ONNX/TensorRT and quantization for efficient inference. Logistics - Location: Redmond (Preferred) or Remote - Duration: <3–6 months> Benefits - Competitive stipend and hands-on projects with measurable real-world impact. - Mentorship from applied scientists and engineers; opportunities to publish and present. - Access to modern GPU infrastructure and a supportive environment for fast, responsible experimentation. - Flexible location and schedule options, subject to team needs. - Rate: $45 per hour

Role Description The Director of Operations, OneForma will drive the day-to-day operational excellence and cross-functional alignment of OneForma’s global platform operations. Reporting directly to the VP of Operations, this role is responsible for managing and developing the operational managers overseeing Community Support, Engagement, Platform Education, and PMO. The ideal candidate combines analytical rigor, strong communication, and people leadership to ensure that these teams deliver measurable impact, operational consistency, and continuous improvement. This role is critical to scaling operational capacity and partnering with executive leadership to execute flagship programs through disciplined management and cross-team coordination. Key Responsibilities - Operational Management & Leadership - Lead and directly manage the team of operational managers (Support, Engagement, Platform Education, PMO). - Provide strategic direction, performance feedback, and career development support to team leads and their direct reports. - Coordinate priorities across teams to ensure alignment with OneForma’s platform goals and annual operations plan. - Serve as the central point of accountability for cross-departmental execution, removing blockers and ensuring communication flow. - Foster a culture of accountability, clarity, and professional growth across all direct-reporting managers. - Coach managers on communication, delegation, and strategic thinking. - Operational Analytics & Performance Management - Own operational performance tracking and reporting across assigned teams. - Partner with PMO and Platform to maintain, expand, and track OneForma Operations KPIs, providing weekly and monthly insights. - Partner with Data and Analytics to extract actionable insights from user, project, and support data. - Establish clear metrics and KPIs for each function (Support resolution rates, Engagement metrics, PMO delivery timelines, Education completion, etc.). - Cross-Team Collaboration & Communication - Serve as the operational connector between internal stakeholders within OneForma Operations. - Ensure smooth coordination of initiatives and timely communication. - Collaborate between PMO, Engagement, Support + Product, Engineering to push those priorities forward. - Maintain visibility into platform governance updates (owned by Engineering), ensuring full visibility in coordination with PMO and Product Success teams. - Process Improvement & Scalability - Identify process inefficiencies and lead continuous improvement initiatives across operations. - Implement systems and tools that improve information flow, reporting consistency, and team coordination. - Support the VP of Operations in executing new strategic programs (e.g., loyalty initiatives, fraud prevention collaboration, or major platform releases). Qualifications - 8–10 years of experience in operations, community or program management, with at least 3 years in a leadership role managing other managers. - Proven ability to lead multi-disciplinary, global teams. - Strong analytical capability with experience using dashboards, KPIs, or data visualization tools (e.g., Power BI, Tableau, Looker). - Exceptional communication and collaboration skills across technical and non-technical stakeholders. - Demonstrated ability to manage competing priorities and maintain operational consistency in a fast-paced environment. Requirements - Experience in digital platforms, crowdsourcing, or community-based ecosystems. - Familiarity with learning platforms, online engagement, or user support operations. - Exposure to PMO or program governance best practices. - Comfort working across time zones and remote-first environments. Key Performance Indicators (KPIs) - Timely delivery of operational programs and PMO projects. - Resolution rates and satisfaction in Support. - Engagement and loyalty metrics. - Completion and impact rates for Platform Success initiatives. - Retention and development of management-level team members. - Efficiency and accuracy of operational reporting. Role Impact This role allows the VP of Operations to focus on strategic growth initiatives — including but not limited to: business financial management and health, fraud prevention, TOF marketing, certification and learning, loyalty strategy, and advanced analytics — while ensuring the operational backbone of the platform runs efficiently, transparently, and at scale. Salary $170,000 Centific is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, citizenship status, age, mental or physical disability, medical condition, sex (including pregnancy), gender identity or expression, sexual orientation, marital status, familial status, veteran status, or any other characteristic protected by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.

• Track, organize, and maintain operational data • Assist in project management • Support daily operations related to data center infrastructure

Role Description For this position, you will be working with one of Centific’s major clients. We are seeking applied scientist interns who possess strong research skills, a proven track record of leading projects related to large language models, and the ability to quickly conceptualize and implement innovative ideas to advance state-of-the-art AI systems. - Keeping a keen eye on the latest developments in the broad AI community. - Working with science, engineering, and program management teams to integrate the latest large language models (LLMs) such as OpenAI models and open-source models into production systems. - Collaborating with other researchers, data scientists, product managers, and engineers in the team to build tools and improve the end-to-end AI Quality of our production systems. - Leveraging data from various sources and domains to design and implement innovative solutions that achieve rigorous metrics and address customer needs. - Effectively communicating and demonstrating work to stakeholders. Qualifications - Currently pursuing a master’s or PhD in Computer Science, Statistics, Electrical or Computer Engineering, or a related technical discipline. - 2+ years of experience in machine learning (ML) or artificial intelligence (AI). - Proficiency with deep learning libraries such as PyTorch or TensorFlow. Requirements - Currently enrolled in a PhD program in Computer Science or related field, with a research focus on natural language processing (NLP), reinforcement learning, deep learning, or related areas. - Publications at top-tier NLP/ML/AI conferences, e.g., NeurIPs, ICML, ICLR, EMNLP, ACL. - Experience in fine-tuning or evaluating large language models (LLMs) or AI agents. Benefits - Rate: $35 per hour. Company Description Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers.