Acceler8 Talent

About the Company

Acceler8 connects the top AI companies with the talent to scale fast, reach milestones, and secure funding so you can launch your AI products with confidence. We're at the forefront of connecting exceptional talent with ground breaking opportunities. We operate as the driving force behind visionary AI startups, actively shaping the future of technology across the Bay Area, Boston, New York, and beyond. Our expertise spans a diverse array of tech specialties, including ML Research & Engineering, Software for ML Platforms, Semiconductor & Chip Design, Silicon Photonics, High Performance Computing, and Machine Learning Compilers. We serve as the catalyst for talent, ensuring that our clients have access to the most qualified professionals to propel their innovations forward. We'll build the team that turns your vision into reality. Are you ready to Acceler8?Contact us today! https://www.acceler8talent.com/contact-us/ _____________________________________________ Important Notice: Scam Alert Targeting Job Seekers We want to inform our network about a scam that is currently targeting job seekers through platforms like WhatsApp and LinkedIn. Please be aware that these messages are not from us or any of our employees. Rest assured, we are actively monitoring this situation and are taking it very seriously. If you have any doubts or concerns, please contact us directly through our official website https://www.acceler8talent.com/ or email us at info@acceler8talent.com. Please do not submit any personal information via links that are not from our official website.

Listed Jobs

Company Name

Acceler8 Talent

Job Title

Software Engineer

Job Description

**Job Title** Software Engineer (Agents) **Role Summary** Design, develop, and scale AI‑driven agents and supporting infrastructure for scientific research platforms. Work cross‑functionally with robotics, machine learning, and scientific teams to build production‑grade tools, data pipelines, and real‑time user interfaces that accelerate materials discovery. **Expectations** - Deliver end‑to‑end agentic solutions from concept to production. - Write clean, type‑checked Python code with asynchronous patterns. - Contribute to both backend systems and responsive front‑end components. - Collaborate effectively with multidisciplinary engineers and scientists. - Maintain high code quality, testing, and documentation standards. **Key Responsibilities** - Build and scale AI agents for scientific superintelligence tasks. - Design and maintain tools for Bayesian optimization, literature search, and experimental database queries. - Develop workflow systems for quantum chemistry simulations. - Create and manage data pipelines for large language model (LLM) ingestion and transformation. - Implement responsive, real‑time front‑end interfaces for agent interaction using Svelte, React, or similar frameworks. - Integrate APIs, data retrieval mechanisms, and code‑execution environments into agentic workflows. - Participate in code reviews, testing, and continuous integration/continuous deployment (CI/CD) processes. **Required Skills** - Strong Python expertise, including async programming, type hinting, and modern AI libraries (e.g., LangChain, Pydantic). - Proven experience building production‑grade agentic workflows (0‑to‑1 development). - Experience with data pipeline construction for LLMs and large‑scale data transformation. - Front‑end development proficiency with Svelte, React, or comparable frameworks. - Familiarity with Bayesian optimization, scientific literature mining, and quantum chemistry simulation concepts (preferred). - Ability to work collaboratively in multidisciplinary teams and communicate technical ideas clearly. **Required Education & Certifications** - Bachelor’s degree in Computer Science, Software Engineering, or a related technical field (Master’s preferred). - Relevant certifications (e.g., Python, Cloud, or AI/ML) are a plus but not mandatory.

New york city, United states

On site

10-11-2025

Company Name

Acceler8 Talent

Job Title

Machine Learning Researcher (LLMs)

Job Description

Job title: Machine Learning Researcher (LLMs) Role Summary: Develop and scale large language model solutions for scientific discovery, creating end‑to‑end pipelines from prototype to production with rigorous, domain‑aware evaluation and close collaboration with multidisciplinary teams. Expectations: - Convert early prototypes into production‑grade systems that enhance scientific workflows. - Design, execute, and interpret extensive experiments and benchmarks. - Communicate findings and requirements effectively to scientists, engineers, and stakeholders. - Maintain a curiosity‑driven, data‑driven mindset with a focus on clear, reproducible research. Key Responsibilities: 1. Design and prototype LLM reasoning, planning, and tool‑use workflows tailored to biological, chemical, and materials science problems. 2. Build custom evaluation frameworks incorporating domain expertise; benchmark models against rigorous metrics. 3. Scale prototypes into scalable, production‑ready systems, integrating continuous feedback loops with research and engineering teams. 4. Lead systematic experimentation, including ablations, hyper‑parameter sweeps, and performance analyses. 5. Translate scientific needs into concrete technical specifications and guide multidisciplinary collaboration. Required Skills: - Deep knowledge of large‑language model architectures, fine‑tuning techniques, and reinforcement learning from human feedback. - Strong research background in machine learning, algorithm development, and statistical evaluation. - Experience deploying distributed training, inference serving, and monitoring for large models. - Proficiency in Python, PyTorch/TensorFlow, and version control/Git workflows. - Ability to design domain‑specific benchmarks and interpret complex results. - Excellent communication skills for writing reports and presenting to scientific audiences. Required Education & Certifications: - Ph.D. or M.S. in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field; equivalent professional experience may be considered. - No mandatory certifications, but familiarity with cloud ML platforms (AWS, GCP, Azure) is advantageous.

Cambridge, United states

On site

08-12-2025

Company Name

Acceler8 Talent

Job Title

Machine Learning Engineer

Job Description

**Job title**: Machine Learning Engineer **Role Summary**: Lead the full lifecycle of machine learning solutions, from concept to production. Design, develop, deploy, and continuously optimize scalable AI models that support high‑performance systems. Work closely with software and systems teams to ensure models are reliable, maintainable, and aligned with product objectives. **Expectations**: - Translate business requirements into technical ML strategies. - Build end‑to‑end AI pipelines that can handle massive workloads with low latency. - Maintain model quality through rigorous monitoring, testing, and iterative improvement. - Collaborate across engineering disciplines to embed ML capabilities into production environments. **Key Responsibilities**: - Develop, train, and fine‑tune ML models using modern frameworks (e.g., PyTorch, TensorFlow). - Deploy models to scalable infrastructure (Docker, Kubernetes, cloud services). - Design and implement monitoring, logging, and alerting for model performance and drift. - Optimize model inference for speed, memory, and cost efficiency. - Integrate models into product workflows and APIs. - Participate in code reviews, architecture discussions, and continuous integration pipelines. **Required Skills**: - Strong programming proficiency in Python; experience with ML libraries (scikit‑learn, PyTorch, TensorFlow, Keras). - Familiarity with model serving frameworks (ONNX, TensorRT, TensorFlow Serving). - Knowledge of containerization (Docker) and orchestration (Kubernetes). - Experience with cloud AI services (AWS AI/ML, GCP AI Platform, Azure ML) or on‑prem deployment. - Ability to design and maintain data pipelines (ETL, stream processing). - Solid understanding of data engineering principles, feature engineering, and model evaluation metrics. - Excellent problem‑solving, communication, and collaboration skills. **Required Education & Certifications**: - Bachelor’s (or higher) degree in Computer Science, Electrical Engineering, Data Science, or related field. - Proven professional experience (≥3 years) in machine learning or AI engineering. - Certifications in cloud AI/ML platforms or relevant technologies are a plus.

Cambridge, United states

On site

08-12-2025

Company Name

Acceler8 Talent

Job Title

Distributed Systems Engineer

Job Description

**Job title:** Distributed Systems Engineer **Role Summary:** Design, build, and operate high-performance distributed data, coordination, and storage systems that support ultra-long‑context AI model training and inference across GPU clusters, ensuring fault tolerance, high availability, and scalability on public cloud platforms. **Expectations:** - Deliver end‑to‑end distributed solutions for large‑scale GPU workloads. - Achieve robust fault detection, automated recovery, and sustained high availability. - Troubleshoot cross‑stack issues involving GPUs, networking, storage, OS, and cloud infra. **Key Responsibilities:** - Architect and implement distributed data and coordination frameworks for ultra‑long‑context model training and inference. - Develop high‑throughput, durable storage and caching layers tailored to GPU infrastructure. - Dive into deep learning framework internals to optimize performance in highly distributed settings. - Build automation tools for monitoring, fault detection, recovery, and scaling across GPU clusters. - Diagnose and resolve complex stack‑wide problems spanning hardware, software, and cloud services. **Required Skills:** - Deep expertise in distributed systems design and operation on public cloud platforms (AWS, GCP, Azure). - Proven experience with highly available, high‑throughput data pipelines and storage. - Strong knowledge of distributed databases, batch or stream processing engines, or distributed file systems. - Hands‑on skill set in GPU hardware, networking, Linux/Unix, and container orchestration (Kubernetes, Docker). - Excellent problem‑solving across the systems stack, with the ability to learn quickly in a frontier environment. **Required Education & Certifications:** - Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field. - Relevant certifications (e.g., AWS Certified Solutions Architect, GCP Professional Cloud Architect) preferred but not mandatory.

San francisco, United states

On site

23-12-2025