Centific Global Solutions

Title: Japanese Localization QA Tester Location: United States Job Description: Part time job requisition id JR107212 About Centific 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. We harness the power of an integrated solution ecosystem—comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets—to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster. 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. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets. About Job Part-time Requirements - Native-level fluency in Japanese language (grammar, vocabulary, composition, punctuation) - Fluency in English (written and spoken) - Experience working in translation - Tech savvy, with experience testing web-based systems and applications on Mac OS X and iOS - Ability to prioritize linguistic issues and distinguish between a true must-fix and a nice-to-have - Experience working with test cases and test scripts - Experience with bug tracking systems - Ability to clearly articulate reproduction steps for a given issue and communicate critical information Rate: $25 per hour 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 Internship: AI Safety, Jailbreaking Attacks & Defense, Agentic AI, Human Behavior (Ph.D. Research Intern) Build the Future of Safe and Responsible AI. Are you advancing the frontiers of AI safety, LLM jailbreak detection and defense, and agentic AI—with publications to show for it? Join us to translate pioneering research into robust security and trustworthy LLM systems that resist adversarial and behavioral exploits. The Mission: We’re tackling cutting-edge AI safety across adversarial robustness, jailbreak defense, agentic workflows, and human-in-the-loop risk modeling. As a Ph.D. Research Intern, you’ll own high-impact experiments from concept to prototype to deployable modules, directly contributing to our platform’s security guarantees. What You’ll Do - Advance AI Safety: Design, implement, and evaluate attack and defense strategies for LLM jailbreaks (prompt injection, obfuscation, narrative red teaming). - Evaluate AI Behavior: Analyze and simulate human-AI interaction patterns to uncover behavioral vulnerabilities, social engineering risks, and over-defensive vs. permissive response tradeoffs. - Agentic AI Security: Prototype workflows for multi-agent safety (e.g., agent self-checks, regulatory compliance, defense chains) that span perception, reasoning, and action. - Benchmark & Harden LLMs: Create reproducible evaluation protocols/KPIs for safety, over-defensiveness, adversarial resilience, and defense effectiveness across diverse models (including latest benchmarks and real-world exploit scenarios). - Deploy and Monitor: Package research into robust, monitorable AI services using modern stacks (Kubernetes, Docker, Ray, FastAPI); integrate safety telemetry, anomaly detection, and continuous red-teaming. Example Problems You Might Tackle - Jailbreaking Analysis: Systematically red-team advanced LLMs (GPT-4o, GPT-5, LLaMA, Mistral, Gemma, etc.), uncovering novel exploits and defense gaps. - Multi-turn Obfuscation Defense: Implement context-aware, multi-turn attack detection and guardrail mechanisms, including countermeasures for obfuscated prompts (e.g., StringJoin, narrative exploits). - Agent Self-Regulation: Develop agentic architectures for autonomous self-check and self-correct, minimizing risk in complex, multi-agent environments. - Human-Centered Safety: Study human behavior models in adversarial contexts—how users probe, trick, or manipulate LLMs, and how defenses can adapt without excessive over-defensiveness. Qualifications - Ph.D. student in CS/EE/ML/Security (or related); actively publishing in AI Safety, NLP robustness, or adversarial ML (ACL, NeurIPS, BlackHat, IEEE S&P, etc.). - Strong Python and PyTorch/JAX skills; comfort with toolkits for language models, benchmarking, and simulation. - Demonstrated research in at least one of: LLM jailbreak attacks/defense, agentic AI safety, human-AI interaction vulnerabilities. - Proven ability to go from concept → code → experiment → result, with rigorous tracking and ablation studies. Requirements - Experience in adversarial prompt engineering, jailbreak detection (narrative, obfuscated, sequential attacks). - Prior work on multi-agent architectures or robust defense strategies for LLMs. - Familiarity with red-teaming, synthetic behavioral data, and regulatory safety standards. - Scalable training and deployment: Ray, distributed evaluation, CI/telemetry for defense protocols. - Public code artifacts (GitHub) and first-author publications or strong open-source impact. Benefits - Real Impact: Your research ships—directly securing our core features and AI infrastructure. - Mentorship: Collaborate with Principal Architects and senior researchers in AI safety and adversarial ML. - Velocity + Rigor: Balance high-quality research with mission-critical product focus. - Rate: $50 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 We are seeking a detail-oriented Spanish Medical Transcriber to transcribe healthcare-related audio recordings into accurate verbatim transcripts. The successful candidate will possess strong Spanish language proficiency, excellent listening skills, knowledge of medical terminology, and the ability to follow established transcription guidelines. Key Responsibilities - Accurately transcribe Spanish medical consultations, dictations, and healthcare-related conversations. - Produce verbatim transcripts while preserving the original meaning and context of spoken content. - Correctly identify and label speakers throughout the transcript. - Ensure accurate segmentation, punctuation, formatting, and timestamping. - Apply transcription guidelines consistently and maintain high quality standards. - Accurately recognize and transcribe medical terminology and clinical language. - Review completed transcripts before submission to ensure quality and completeness. - Meet assigned productivity and turnaround time expectations. Qualifications - Native or near-native proficiency in Spanish. - Strong written communication skills in Spanish. - Experience in medical transcription, healthcare documentation, or healthcare language services preferred. - Familiarity with medical terminology, anatomy, medications, and clinical workflows. - Excellent attention to detail and listening comprehension skills. - Ability to work independently and meet productivity targets. Preferred Qualifications - Previous experience with healthcare transcription projects. - Understanding of speaker diarization and multi-speaker transcription. - Exposure to HIPAA/PHI handling requirements. - Experience working with transcription platforms and annotation tools. Key Performance Indicators (KPIs) - Transcription accuracy - Speaker attribution accuracy - Adherence to transcription guidelines - Productivity targets - Quality audit scores Skills - Spanish Language Proficiency - Medical Terminology - Transcription & Proofreading - Attention to Detail - Time Management - Quality Focus

• Ensure timely SLA-based resolution of server fault tickets • Manage OS reboot, reinstallation and recovery • Handle on-call tickets and operations recovery management

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.