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ai inference data engineer

Dizzaract FZ LLC

About DizzaractDizzaract is a UAE-based game development studio founded in 2022, headquartered at Yas Creative Hub, Abu Dhabi. We develop cutting-edge AI-powered games and systems, including our innovation R&amp;D laboratory FAR labs, the upcoming hero shooter Farcana, and the AI gaming identity platform GAMED. Our research and development team boasts over 100 peer-reviewed papers and more than 20 patents in AI-driven gameplay, digital ownership, and competitive design. With a diverse team of more than 80 professionals from over 20 countries, we are committed to innovation, excellence, and building a culture that drives performance and results.The Mission: An inference network routing millions of requests globally generates a massive, complex data exhaust. You will build the data plane that fuels our routing intelligence, telemetry, and distributed memory systems. To beat OpenRouter, our network needs to route requests intelligently based on real-time hardware metrics and cost analysis without adding latency.What You Will Do:<ul><li>High-Throughput Telemetry: Design pipelines to ingest, process, and analyze millions of telemetry events per second (GPU utilization, TTFT, inter-token latency) from distributed nodes.</li><li>Distributed KV-Cache Architecture: Architect the data layer for distributed KV-cache storage and retrieval, allowing the network to context-switch efficiently across different compute nodes.</li><li>Intelligent Routing State: Build the real-time data stores that power our routing layer, ensuring the network always knows the exact state, cost, and availability of every node globally.</li><li>Ledger &amp; Analytics: Develop the backend pipelines for billing, rate-limiting, and auditing, ensuring airtight data consistency for high-frequency micro-transactions.</li><li>Data Packaging: Ensure all data infrastructure deployments are containerized, immutable, and require zero manual configuration upon deployment.</li></ul>What We Are Looking For:<ul><li>Expertise in high-throughput messaging and streaming systems (e.g., Redpanda, Kafka) and real-time OLAP databases (e.g., ClickHouse).</li><li>Strong proficiency in backend languages (Rust, Go, or Python) with a focus on high concurrency and low latency.</li><li>Experience with vector databases and managing massive, distributed state.</li><li>A strong grasp of distributed consensus algorithms and data replication across decentralized environments.</li></ul>Work Location: In person

AI Inference Data Engineer

YO IT Consulting

<div>
 
 Job Title:
 
 AI/ML Engineer
 
 
 
 Job Type:
 
 Full-Time
 
 
 
 Job Summary
 
 
 
 Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to proprietary AI infrastructure, you&rsquo;ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You&rsquo;ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.
 </li>
 <li>
 Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.
 </li>
 <li>
 Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
 </li>
 <li>
 Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
 </li>
 <li>
 Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
 </li>
 <li>
 Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).
 </li>
 <li>
 Document technical decisions and communicate complex concepts clearly to both technical and non-technical stakeholders.
 
 
 </li>
 </ul>
 
 Required Skills And Qualifications
 
 
 
 <ul>
 <li>
 Proficiency in Python for AI/ML development, including experience with REST APIs and SDK integration.
 </li>
 <li>
 Hands-on experience with LLMs, RAG systems, and prompt engineering in production environments.
 </li>
 <li>
 Familiarity with multi-agent orchestration, tool use, and frameworks like LangGraph and LangChain.
 </li>
 <li>
 Deep understanding of cloud AI services (AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock).
 </li>
 <li>
 Background in building and maintaining data pipelines, ontologies, metadata catalogs, and ETL processes.
 </li>
 <li>
 Strong grasp of secure coding and modern DevOps practices (CI/CD pipelines).
 </li>
 <li>
 Exceptional written and verbal communication skills for effective collaboration and documentation.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with AI/agentic platforms, such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise.
 </li>
 <li>
 Knowledge of metadata catalog platforms (MCP) and advanced API development techniques.
 </li>
 <li>
 Prior exposure to government or highly regulated cloud environments and compliance standards.
 </li>
 </ul>
</div>

AI/ML Engineer - Remote

About DizzaractDizzaract is a UAE-based game development studio founded in 2022, headquartered at Yas Creative Hub, Abu Dhabi. We develop cutting-edge AI-powered games and systems, including our innovation R&amp;D laboratory FAR labs, the upcoming hero shooter Farcana, and the AI gaming identity platform GAMED. Our research and development team boasts over 100 peer-reviewed papers and more than 20 patents in AI-driven gameplay, digital ownership, and competitive design. With a diverse team of more than 80 professionals from over 20 countries, we are committed to innovation, excellence, and building a culture that drives performance and results.Role SummaryWe are seeking a strategic Business Developer with deep expertise in AI models, inference, and MLOps commercialization. You will be responsible for identifying, negotiating, and closing B2B partnerships to monetize our proprietary AI models and inference capabilities. This role sits at the intersection of technology and business &mdash; you will translate complex AI technical value (latency, throughput, model accuracy, cost per inference) into revenue-generating opportunities.Key Responsibilities1. AI Business Development &amp; Partnerships<ul><li>Identify and secure partnerships with enterprises, developers, and platforms needing AI inference solutions (LLMs, computer vision, generative AI for gaming).</li><li>Build a go-to-market strategy for FAR Labs&rsquo; proprietary AI models and inference infrastructure.</li><li>Develop licensing models: API calls, subscription tiers, on-prem inference, or revenue-share agreements.</li><li>Lead the full sales cycle: lead generation, technical scoping, proposal writing, contract negotiation, and closing.</li></ul>2. Monetization of Inference &amp; Model APIs<ul><li>Collaborate with engineering to define pricing strategies based on inference cost (compute, tokens, latency, batch size).</li><li>Package our R&amp;D output (20+ patents, 100+ papers) into sellable AI products: game AI agents, player behavior models, identity verification AI (GAMED).</li><li>Create technical marketing materials: case studies, inference benchmarks, model cards, and demos.</li></ul>3. Market &amp; Competitive Intelligence<ul><li>Track the AI inference landscape: cloud providers (AWS Bedrock, Azure AI, Replicate), open-source models, and emerging competitors.</li><li>Identify gaps where Dizzaract&rsquo;s models outperform in latency, cost, or domain-specific tasks (competitive gaming, real-time AI).</li><li>Provide feedback to R&amp;D on market needs (model size, quantization, edge inference requirements).</li></ul>4. Customer &amp; Technical Engagement<ul><li>Serve as the bridge between external clients and our ML engineering team &mdash; translate business needs into technical requirements (batch vs real-time inference, GPU/CPU tradeoffs, SLAs).</li><li>Support clients with POCs, integration of our inference APIs, and performance validation.</li><li>Collect and prioritize feature requests for our inference stack (scaling, observability, versioning).</li></ul>5. Strategic Growth &amp; OKRs<ul><li>Define and track BD KPIs: number of active partnerships, monthly recurring inference revenue (MRR), customer acquisition cost (CAC), and gross margin per inference.</li><li>Implement a quarterly OKR framework for the BD team aligned with company revenue goals.</li><li>Report directly to COO and the Director of BD on pipeline, forecasts, and strategic deals.</li></ul>Required Qualifications &amp; Skills<ul><li>3+ years in business development, partnerships, or technical sales focused on AI/ML models or inference platforms.</li><li>Strong understanding of inference concepts: model serving, batching, latency vs throughput, token-based pricing, fine-tuning, and quantization.</li><li>Ability to read basic API docs and discuss model performance with engineers (no need to code, but technical fluency is a must).</li><li>Proven track record of closing B2B SaaS or API-based deals, preferably with gaming, media, or security clients.</li><li>Familiarity with AI deployment tools (Hugging Face, TensorRT, vLLM, or cloud inference endpoints) is a strong plus.</li><li>Excellent negotiation, communication, and presentation skills for technical and non-technical audiences.</li><li>Self-starter mindset, comfortable with remote work and fast-paced R&amp;D environments.</li></ul>Final NoteThis role is for a business-savvy AI expert who wants to turn cutting-edge research into real revenue. You will have direct access to 20+ patents, a world-class R&amp;D team, and an emerging AI ecosystem in Abu Dhabi. If you understand inference pricing models, can sell APIs to developers and enterprises, and want to shape the commercial future of AI in gaming &mdash; this is your opportunity.Work Location: In person

Business Developer Executive

Inception

<div>
 Inception, a G42 company, is the region&rsquo;s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer &ndash; transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact. For more information, please visit www.inceptionai.ai
 
 
 
 Overview
 
 
 
 Inception is seeking a highly skilled Lead Data Engineer to architect and build scalable, cloud-native data and AI pipelines that power enterprise LLM, RAG, and retrieval systems.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and optimize scalable data pipelines for AI/LLM workloads, including vectorization and embedding processing.
 </li>
 <li>
 Develop and maintain ETL/ELT workflows for structured, unstructured, and streaming data.
 </li>
 <li>
 Create and manage vector database indexing and similarity search pipelines using tools like FAISS, Pinecone, Weaviate, Qdrant, Chroma.
 </li>
 <li>
 Build retrieval systems for RAG, semantic search, and enterprise knowledge retrieval.
 </li>
 <li>
 Develop robust, reusable data orchestration pipelines using Airflow, Spark, or similar tools.
 </li>
 <li>
 Architect and manage data pipelines across Azure (primary), AWS, and GCP environments.
 </li>
 <li>
 Integrate and optimize storage and processing across SQL, NoSQL, and vector databases.
 </li>
 <li>
 Contribute to the design and implementation of event-driven architectures.
 </li>
 <li>
 Collaborate with AI teams to enable embedding generation, LLM integration, and model-serving pipelines.
 </li>
 <li>
 Ensure end-to-end data quality, monitoring, reliability, and observability.
 </li>
 <li>
 Lead or participate in system design for large-scale, distributed data and AI systems.
 
 
 </li>
 </ul>
 
 Required Skills
 
 
 
 
 Programming &amp; Data
 
 
 
 <ul>
 <li>
 Strong expertise in Python for data processing, APIs, automation, or distributed workloads.
 </li>
 <li>
 Strong proficiency in SQL and knowledge of NoSQL databases (MongoDB, DynamoDB, Cosmos DB, etc.).
 </li>
 <li>
 Experience with vector databases, such as: FAISS, Pinecone, Weaviate, Qdrant, Chroma.
 </li>
 <li>
 Strong knowledge of data modeling, pipeline development, and ETL/ELT frameworks.
 
 
 </li>
 </ul>
 
 AI/LLM Infrastructure
 
 
 
 <ul>
 <li>
 Solid understanding of vectorization, embeddings, and similarity search techniques.
 </li>
 <li>
 Familiarity with LLMs, embedding models, and RAG pipeline concepts.
 </li>
 <li>
 Experience integrating embedding-generation pipelines via Hugging Face, OpenAI, or other model providers.
 
 
 </li>
 </ul>
 
 Cloud &amp; Distributed Systems
 
 
 
 <ul>
 <li>
 Proficiency with Azure (primary), and familiarity with AWS and GCP.
 </li>
 <li>
 Experience with Docker and containerized development.
 </li>
 <li>
 Understanding of Kubernetes is a strong plus.
 
 
 </li>
 </ul>
 
 Orchestration &amp; Big Data
 
 
 
 <ul>
 <li>
 Expertise in Apache Airflow for scheduling and orchestration.
 </li>
 <li>
 Experience with Apache Spark or equivalent distributed processing frameworks.
 
 
 </li>
 </ul>
 
 Architecture &amp; Engineering Fundamentals
 
 
 
 <ul>
 <li>
 Strong system design fundamentals for scalable and distributed systems.
 </li>
 <li>
 Knowledge of event-driven architecture and modern data platforms.
 </li>
 <li>
 Strong understanding of DevOps, CI/CD, version control, and observability best practices.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 8+ years of progressive experience in data engineering, distributed systems, or AI/ML data infrastructure
 </li>
 <li>
 Experience building RAG pipelines in production.
 </li>
 <li>
 Knowledge of graph databases or hybrid search systems.
 </li>
 <li>
 Understanding of model deployment, inference optimization, and caching techniques for LLM workloads.
 </li>
 <li>
 Familiarity with data governance, IAM, and security patterns across cloud ecosystems
 
 
 </li>
 </ul>
 What We Look For
 
 
 If you are a performance-driven, inquisitive mind with the agility to adapt to ambiguity, you will fit right in. You should be eager to explore opportunities to build meaningful collaborations with stakeholders and aspire to create unique customer-centric solutions. Bias for action and a passion to conquer new frontiers in the AI space is at the heart of the Inception community.
 
 
 What Working At Inception Offers
 
 
 Culture: An open, diverse and inclusive environment with a global vision that encourages personal growth and focuses on ground-breaking, industry-first innovations.
 
 
 Career: Outstanding learning, development &amp; growth opportunities via structured training programs and innovative, high-tech projects.
 
 
 Rewards: A competitive remuneration package with a host of perks including healthcare, education support, leave benefits and more.
 
 
 If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.
</div>

Lead Data Engineer

About DizzaractDizzaract is a UAE-based game development studio founded in 2022, headquartered at Yas Creative Hub, Abu Dhabi. We develop cutting-edge AI-powered games and systems, including our innovation R&amp;D laboratory FAR labs, the upcoming hero shooter Farcana, and the AI gaming identity platform GAMED. Our research and development team boasts over 100 peer-reviewed papers and more than 20 patents in AI-driven gameplay, digital ownership, and competitive design. With a diverse team of more than 80 professionals from over 20 countries, we are committed to innovation, excellence, and building a culture that drives performance and results.The Mission: We are building a highly optimized, decentralized AI inference network. To beat the latency and throughput of established centralized players, we cannot rely on off-the-shelf wrappers. You will be responsible for building the bare-metal, ultra-low-latency infrastructure that serves large language models and multimodal networks at unprecedented scale.What You Will Do:<ul><li>Core Engine Development: Architect and write highly optimized, low-level code (primarily in Rust and C) to manage model loading, memory allocation, and request batching across a distributed fleet of GPUs/NPUs.</li><li>Hardware-Aware Optimization: Implement tensor mathematics optimizations and custom kernels (CUDA/Triton) to squeeze maximum FLOPS out of the hardware.</li><li>Zero-Intervention Deployments: Build rock-solid, fully packaged infrastructure pipelines. We operate with zero manual intervention&mdash;no ad-hoc scripts, no PowerShell bandaids. If a node fails, the network must heal autonomously.</li><li>Decentralized Orchestration: Design the peer-to-peer or decentralized routing logic that ensures high availability and optimal load balancing across geographically distributed nodes.</li><li>Advanced Inference Techniques: Implement and optimize techniques like continuous batching, speculative decoding, and paged attention (vLLM, TensorRT-LLM) customized for our specific network architecture.</li></ul>What We Are Looking For:<ul><li>Deep expertise in systems programming (Go) and a strong aversion to bloated, high-level abstractions where performance matters.</li><li>Proven experience with GPU programming (CUDA, ROCm) and low-level hardware architecture.</li><li>Strong understanding of deep learning architectures (Transformers, Mamba) and how tensor operations execute on silicon.</li><li>Experience building highly concurrent, distributed systems with sub-millisecond network latency requirements.</li></ul>Work Location: In person

AI Inference Infrastructure Engineer

Qualcomm

<div><h2 class="jobSectionHeader">Company:
</h2>Qualcomm Engineering FZ LLC
<h2 class="jobSectionHeader">Job Area:
</h2>Engineering Group, Engineering Group &gt; Software Applications Engineering
General Summary:
About Qualcomm IE‑IoT
 
Qualcomm is a global leader in connected intelligent edge platforms, delivering solutions that combine high‑performance compute, connectivity, and AI across industries including industrial automation, smart cities, energy, and public sector. The IE‑IoT business unit enables secure, scalable, low‑latency intelligence across on‑device, on‑premises, and hybrid cloud deployments.
Role Summary
 
The IoT Solutions Engineering Lead is a senior, hands‑on technical leadership role responsible for defining, architecting, and delivering end‑to‑end IoT and Edge AI solutions built on Qualcomm platforms. This role sits at the intersection of solution architecture, customer engineering, product management, and ecosystem partnerships, owning reusable solution blueprints that accelerate customer adoption across multiple verticals while serving as a trusted technical advisor to strategic customers.
<div></div>Key Responsibilities
Solution Architecture &amp; Technical Leadership
<ul><li>Define and own scalable IoT and Edge AI solution blueprints for priority verticals
</li><li>Architect end‑to‑end systems spanning on‑device compute, AI acceleration (CV, GenAI, multimodal), connectivity, gateways, edge servers, and hybrid cloud integrations
</li><li>Produce reference architectures, design guides, and deployment playbooks
</li><li>Ensure solutions meet production requirements for performance, latency, power, thermals, security, privacy, and scalability
</li></ul>Customer &amp; Partner Engagement
<ul><li>Act as technical lead and trusted advisor for strategic customers from discovery through production
</li><li>Translate business use‑cases and KPIs into system‑level technical architectures
</li><li>Lead executive‑level architecture reviews and roadmap alignment
</li><li>Collaborate with OEMs, ISVs, system integrators, and cloud partners
</li><li>Support POCs, pilots, and commercial launches
</li></ul>Hands‑On Prototyping &amp; Validation
<ul><li>Lead system bring‑up, prototyping, benchmarking, and optimization
</li><li>Integrate workloads such as computer vision, video analytics, AI/ML inference (CNNs, LLMs, VLMs), IoT gateways, and industrial data pipelines
</li><li>Profile and optimize end‑to‑end behavior across latency, throughput, accuracy, power, and cost on Qualcomm AI‑enabled platforms
</li></ul>Hybrid Edge AI Architecture
<ul><li>Design distributed AI architectures across on‑device, on‑prem edge, and cloud
</li><li>Enable offline/online operation, observability, fleet management, and secure enterprise integration
</li></ul>Cross‑Functional Leadership
<ul><li>Partner with Product Management, hardware/software engineering, performance teams, and customer engineering
</li><li>Feed real‑world deployment insights into platform, SDK, and roadmap improvements
</li><li>Represent Qualcomm in customer workshops and industry forums
</li></ul>Technical Profile
<ul><li>Strong system‑level expertise in IoT, embedded systems, and Edge AI
</li><li>Hands‑on software experience in Python and/or C/C++
</li><li>Experience with Embedded Linux, containers (Docker, Kubernetes), AI frameworks/runtimes (TensorFlow, PyTorch, ONNX, Qualcomm AI tools)
</li><li>Background in computer vision and/or generative AI inference
</li><li>Connectivity knowledge: Wi‑Fi, Bluetooth, Ethernet, LTE/5G
</li></ul><div></div>Preferred Experience
<ul><li>Delivering production IoT or Edge AI systems in customer‑facing roles
</li><li>Vertical exposure in industrial, smart cities, retail, healthcare, logistics, or public sector
</li><li>Hybrid edge/cloud architectures
</li><li>Executive‑level communication and product roadmap influence through deployments
</li></ul>What's on Offer
Apart from working with great people, we offer the below:
<ul><li>Salary including housing &amp; transport allowance
</li><li>Stock (RSU's) and performance related bonus
</li><li>16 weeks fully paid Maternity Leave
</li><li>6 weeks fully paid Paternity Leave
</li><li>Employee stock purchase scheme
</li><li>Child Education Allowance
</li><li>Relocation and immigration support (if needed)
</li><li>Life and Medical Insurance
</li><li>Live+ Well Reimbursement for health and recreational membership fees
</li></ul>Minimum Qualifications:
<ul><li>Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Software Applications Engineering, Software Development experience, or related work experience.
</li></ul>OR
 
Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Software Applications Engineering, Software Development experience, or related work experience.
 
OR
 
PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Software Applications Engineering, Software Development experience, or related work experience.
 
 
<ul><li>4+ years of experience with Programming Language such as C, C++, Java, Python, etc.
</li><li>4+ years of experience with debugging techniques.
</li></ul>*References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
<div>Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
</div>Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
If you would like more information about this role, please contact Qualcomm Careers .</div>

IoT Solutions Engineering Lead - Abu Dhabi, UAE

GenBio AI

<div>
 GenBio AI develops multiscale foundation models to decode and simulate human biology. Our team is accelerating towards an ambitious future where scientists can unlock humanity's biggest challenges in drug discovery, healthcare, and fundamental research with AIDO (AI-Driven Digital Organism): a unified framework for predicting, simulating, and programming biology across all scales. The foundation of this vision begins today as we engineer the virtual cell to model and simulate the fundamental unit of life.
 
 
 This vision has brought together a talent-dense group of product-minded researchers and engineers dedicated to bringing it to reality. Our team prides itself on our strong engineering culture and highly interdisciplinary and collaborative approach. We are based in Palo Alto, with satellite offices in Paris and Abu Dhabi.
 
 
 As our data ingestion needs grow, we are looking for a Bioinformatics Data Engineer to act as the crucial bridge between raw biological data and our scalable infrastructure. Reporting to the Data Engineering Lead, you will leverage your deep biological domain expertise to build the initial scripts and processing logic for complex datasets, ensuring they are primed for large-scale foundation model training.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Source &amp; Acquire Biological Data - Identify, evaluate, and obtain high-quality bioinformatics datasets from public and partner sources (e.g., NCBI, PubChem, ENCODE,UniProt etc.) to support research and model development initiatives
 </li>
 <li>
 Deeply Understand Complex Datasets - Develop a comprehensive understanding of biological datasets, including data structures, schemas, metadata standards, entity relationships, and underlying biological context to ensure accurate interpretation and usage
 </li>
 <li>
 Design &amp; Implement Data Processing Pipelines - Develop robust preprocessing scripts and scalable data transformation workflows using Python, R, and relevant Tools. Leverage AI-assisted tools where appropriate to process, clean, normalize, and integrate complex biological data for foundation model training
 </li>
 <li>
 Structure &amp; Standardize Biological Data - Organize heterogeneous datasets into well-defined, interoperable formats aligned with internal infrastructure requirements and downstream AI training pipelines
 </li>
 <li>
 Bioinformatics Data Analysis - Perform exploratory and statistical analysis of genomic, transcriptomic, proteomic, and other multi-omics datasets to assess data quality, uncover biological patterns, and generate insights that inform model development. Apply appropriate computational and statistical methods to validate assumptions and support downstream AI training and evaluation
 </li>
 <li>
 Build Data Products - Create production-ready data assets, including standardized datasets, curated releases, dashboards, analytical reports, and technical documentation to enable efficient research and model evaluation
 </li>
 <li>
 Ensure Data Quality &amp; FAIR Compliance - Curate, annotate, validate, and standardize public and partner datasets in alignment with FAIR (Findable, Accessible, Interoperable, Reusable) principles, ensuring long-term usability and reproducibility
 </li>
 <li>
 Collaborate Cross-Functionally - Partner closely with research scientists and ML engineers to translate biological research needs into scalable data engineering solutions that support AI model training and evaluation
 </li>
 <li>
 Knowledge Sharing &amp; Documentation - Contribute domain expertise by documenting data methodologies, maintaining clear technical documentation, and sharing biological data insights across teams
 
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Educational Background: Bachelor&rsquo;s or Master&rsquo;s degree in Bioinformatics, Computational Biology, Computer Science, or a related field with a heavy focus on the life sciences
 </li>
 <li>
 Biological Data: Deep, hands-on familiarity with multiple biomedical data modalities (e.g., genomics, transcriptomics, spatial omics, protein structure, biomedical imaging, clinical/phenotypic data, etc.)
 </li>
 <li>
 Biological Tools: Familiar with Bioconda,Biopython,Bioconductor, samtools,bamtools,bcftools,gffutils etc
 </li>
 <li>
 Scripting &amp; Tooling: Strong programming skills in Python (Pandas, NumPy) and proficiency with standard bioinformatics workflow managers and tools (e.g., Ray, Kubeflow)
 </li>
 <li>
 Engineering Handoff: Experience writing clean, modular code that can be easily picked up by core data engineers for optimization in cloud environments (AWS/GCP/HF) and containerized setups (Docker)
 </li>
 <li>
 AI/ML Awareness: A solid understanding of machine learning workflows and how biological data must be formatted and batched for deep learning frameworks (e.g., PyTorch)
 
 
 
 
 </li>
 </ul>
 Join us as we embark on this journey to redefine the future of biology and medicine.
 
 
 We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. GenBio AI participates in the U.S. Department of Homeland Security&rsquo;s E-Verify program to confirm the employment eligibility of all newly hired employees. For more information on E-Verify, please visit www.e-verify.gov.
 
 
 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
</div>

Bioinformatics Data Engineer

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