AI Jobs

Other Requirements:

• Send resume at given email

Other Requirements:

• Send your resume at email address provided

Benefits:

• Build infrastructure from the ground up - not maintain decades-old systems

• Work on problems that matter - real enterprise deployments with real consequences

• Learn by doing - tackle challenges that require creative problem-solving, not following runbooks

• Direct impact on product and customers - see your work in production in days, not months

• Equity stake in what we're building together

Experience Requirements:

• 5+ years of experience as a DevOps engineer or in similar infrastructure roles

• Hands-on experience building and maintaining production cloud infrastructure

• Experience supporting applications in production environments

Other Requirements:

• Strong hands-on experience with AWS cloud services and architecture patterns

• Proficiency with Docker and solid experience with Kubernetes for container orchestration

• Experience implementing observability and error tracking solutions (such as Datadog, New Relic, or similar)

• Solid scripting and automation skills using Python or Bash

• Hands-on experience with Infrastructure-as-Code using Terraform

• Solid understanding of networking, security groups, load balancers, and DNS

• Experience building and maintaining CI/CD pipelines using tools like GitHub Actions, GitLab CI, or similar

• Proficiency with Git and Linux system administration

• Database operations experience supporting production systems

• Strong problem-solving skills and ability to work effectively in fast-paced environments

• Excellent verbal and written communication skills

• Comfort with changing priorities and ability to adapt quickly

Responsibilities:

• Build and maintain cloud infrastructure on AWS

• Implement and optimize CI/CD pipelines to support smooth software delivery

• Deploy and manage containerized applications using Docker and Kubernetes

• Implement Infrastructure-as-Code using Terraform for provisioning and configuration management

• Monitor system performance and application health using modern observability and error tracking platforms

Education Requirements:

• PhD candidate

Other Requirements:

• EU-funded

Responsibilities:

• Prostate Research

• Computational biology

Education Requirements:

• PhD candidate

Other Requirements:

• EU-funded

Responsibilities:

• Kidney Research

• Computational biology

Benefits:

• Opportunity to work on impactful, data-centric projects

• Exposure to both data analytics and data science practices

• Gain hands-on experience with cutting-edge technologies

• Collaborative and growth-oriented work environment

Education Requirements:

• Currently pursuing or recently completed a degree in Computer Science, Data Science, Statistics, or a related field

Experience Requirements:

• Basic knowledge of data analytics concepts and methods (e.g., statistical analysis, data visualization)

• Proficiency in data analysis tools such as Excel, SQL, and Python (Pandas, NumPy, etc.)

Other Requirements:

• Strong problem-solving skills and attention to detail

• Ability to work independently and in a team environment

• Excellent communication skills with the ability to present data findings clearly

• Knowledge of data visualization tools (e.g., Tableau, Power BI) and PostgreSQL is a Bonus

• A willingness to learn new tools and technologies in data science

Responsibilities:

• Assist in the collection, processing, and cleaning of large datasets to ensure data quality and integrity

• Perform basic data analysis using tools such as Excel, SQL, and Python to generate actionable insights

• Support the development and testing of machine learning models under guidance

• Work closely with engineering and business teams to identify opportunities for data-driven improvements

• Contribute to the preparation and presentation of data reports and dashboards

Other Requirements:

• Legally authorized to work in the United States

• Willing to work in-office five days a week

Benefits:

• Flexible hours to fit class schedule

• Team lunches on Mondays and Wednesdays

• Office snacks and drinks

Education Requirements:

• Engineering or technical students preferred

Experience Requirements:

• Experience with electromechanical assembly is a plus

• Experience with 3D printing is a plus

Other Requirements:

• Detail-oriented and organized

• Basic computer and spreadsheet skills

• Good communication and teamwork

Responsibilities:

• Assemble and test small components and sub-assemblies

• Organize and maintain assembly and inventory spaces

• Provide feedback on process improvements

• Record data and assist with tracking production progress

• Collaborate with team members

Experience Requirements:

• 3+ years assembly or equivalent experience in electro-mechanical projects

• Organizational skills and detail-oriented

• Excellent written and oral communication skills

• Competency in Word, Excel, and PowerPoint

Other Requirements:

• Experience with inventory management software is a plus

• Experience with assembly line setup is a plus

• Experience with 3D printers

Responsibilities:

• Assemble electromechanical and optical sub-assemblies

• Perform go/no-go diagnostic tests on products

• Maintain component inventory

• Manage and maintain 3D printers for prototyping

Education Requirements:

• Doctoral degree (PhD) in a technical or scientific field (AI, machine learning, signal/speech/image processing, NLP)

• Proven scientific achievements and publications in peer-reviewed journals or international publications

Experience Requirements:

• Experience working with quality management systems (QMS) in software or medical devices

• Experience with ISO 13485, ISO 14971, and IEC 62304 standards

• Participation in the preparation of technical and quality documentation for clinical trials or certification processes

Other Requirements:

• Knowledge of modern machine learning and deep learning methods (CNN, sequential models, NLP, behavior analysis)

• Knowledge of explainable artificial intelligence (XAI) and model interpretability

• Knowledge of AI system design, evaluation, and testing (security, risk, bias, fairness, ethical aspects)

• Knowledge of GDPR and Good Clinical Practice (GCP)

Responsibilities:

• Overseeing the development and validation of AI algorithms and their integration into medical device software

• Ensuring compliance of software development processes with QMS and relevant standards

• Collaborating with the R&D team to define requirements for AI components

• Co-creating and reviewing technical and quality documentation for registration and clinical trials

• Participating in design reviews, internal audits, and preparing for external audits

Education Requirements:

• Computer Science degree

• Computer Engineering (CE) degree

• Electrical Engineering (EE) degree

Experience Requirements:

• 5-10 years preferred (3+ years considered)

• Strong backend engineering experience with Python

• Experience at a seed-stage or Series A startup

• Experience with geometric, spatial, or simulation-related data

• Experience with GPU computing, LLM/agentic systems, or data-heavy pipelines

Other Requirements:

• No visa sponsorship

• Comfortable contributing to React + TypeScript codebases

• Exposure to infrastructure (cloud, CI/CD, containers, DevOps)

Responsibilities:

• Own major components of backend systems

• Build performant, production-grade backend features in Python

• Work with geometry, spatial data, simulation data, and large datasets

• Contribute to frontend components in React + TypeScript

• Collaborate on data pipelines, GPU-related workflows, and LLM/AI-driven functionality

Experience Requirements:

• 5+ years of professional experience in software engineering or data engineering

• Strong programming skills in Python and Golang

• Deep understanding of SQL and modern data lake architectures

• Hands-on experience with AWS services

• Proficiency with Terraform

Other Requirements:

• S3

• Lambda

• Glue

• Kinesis

• Athena

• RDS

• Argo Workflows

• Parquet

• Iceberg

• Delta Lake

• Kafka

• IaC

Responsibilities:

• Design and build high-throughput data ingestion pipelines

• Implement secure data lake and SQL-based storage architectures

• Develop internal tools and frameworks using Python and Golang

• Collaborate cross-functionally to define data contracts and schemas

• Manage infrastructure using Terraform and AWS services

Education Requirements:

• M.S. or Ph.D. in Computer Science, AI, Machine Learning, or a related field

• Specialization in NLP or deep learning

Experience Requirements:

• 5+ years of experience in machine learning or AI

• Focus on NLP, LLMs, or conversational AI

• Experience building production grade RAG pipelines

• Fluency with prompt engineering or instruction tuning

• Deep understanding of document retrieval and vector stores

Other Requirements:

• LangChain

• LlamaIndex

• FAISS

• Weaviate

• Pinecone

• PyTorch

• Hugging Face

• LLAMA

• Mistral

• Claude

• GPT

• Agentic RAG

Responsibilities:

• Lead architecture and development of RAG systems

• Develop AI-powered assistants for industrial troubleshooting

• Build pipelines to ingest and index large document corpora

• Fine-tune foundational models for domain-specific logic

• Design evaluation strategies for system performance

Education Requirements:

• M.S. or Ph.D. in Electrical Engineering, Computer Science, or related field

• Focus on signal processing, time-series analysis, and machine learning

Experience Requirements:

• 5+ years developing signal processing and ML solutions for sensor data

• Track record of bringing at least one ML solution to market

• Deep understanding of digital signal processing (DSP) methods

• Experience with RNNs, LSTMs, and temporal convolutional networks

• Experience with physical sensors like IMUs and microphones

Other Requirements:

• PyTorch

• TensorFlow

• Keras

• FFT

• Filtering

• Activity recognition

• Anomaly detection

• Edge deployment

Responsibilities:

• Design real-time signal processing and ML pipelines

• Develop models for classification, prediction, and pattern analysis

• Research and implement RNN and temporal transformer architectures

• Collaborate with hardware and embedded teams for integration

• Optimize signal-processing techniques for model input quality