Top Tech Jobs & Startup Jobs in Austin, TX

Remote entry-level NLP engineering role focused on building language processing pipelines. Responsibilities include fetching unstructured text/audio data, preparing data with NLTK/spaCy/Gensim/Librosa, and developing complex deep learning models (CNNs, RNNs, MLPs, autoencoders) in TensorFlow or PyTorch for classification, regression, clustering, anomaly detection and structured outputs.

Remote entry-level DevOps role responsible for deploying and managing containerized Python and JavaScript applications on cloud managed services (AWS/Azure/GCP). Implement CI/CD pipelines, container orchestration (Kubernetes/EKS/AKS/GKE), deploy web and microservice applications, node/django apps, and managed databases. Opportunity to work on data and ML infrastructure and scale deployments.

Develop and maintain Express.js web applications and complex RESTful APIs. Write JavaScript from scratch, design advanced SQL/NoSQL queries, handle nested JSON/XML, ensure API security and scalability, and collaborate with data engineering on data-platform products.

Develop and maintain high-volume Kafka data ingestion pipelines in Python using Producer/Consumer APIs and Kafka Connect (Debezium/JDBC). Configure topics, brokers, schema registry, converters, and connectors; implement CDC, custom producer/consumer logic and transformations; optimize broker/producer/consumer/connect/stream settings; deploy multiple source/sink connectors to production and integrate Kafka with messaging systems like RabbitMQ, Redis, and AWS SQS.

Build and maintain backend APIs and microservices using Django REST Framework and Django 3.0. Implement serialization, models, views, routers, authentication/authorization, and complex RESTful endpoints. Work with relational and NoSQL databases, complex SQL queries, nested JSON and XML, and ensure API security and scalability. Collaborate with data engineering on data and ML pipelines. Immediate joiners; remote, individual-contributor role in a startup-like environment.

Remote entry-level data science engineer role building end-to-end data science applications: data preparation, exploration, feature engineering, modeling, automation, and distributed model implementations using Python, SQL and scalable paradigms (MapReduce/PySpark). Must show real-world full-cycle project experience and readiness to learn PySpark quickly.

Develop and maintain production-grade PySpark data and ML pipelines: ingest from multiple sources, implement distributed algorithms and complex SQL, optimize performance, integrate APIs/streams/files, and collaborate with data science to deploy scalable solutions.

Hands-on DevOps role focused on containerization and cloud deployments: build and deploy Docker images across VMs, container services, and Kubernetes; implement CI/CD pipelines; manage identity services and APIs; deploy web apps and microservices on AWS/Azure/GCP; monitor container logging and manage managed databases. Work as an individual contributor on production platforms.

Remote entry-level Big Data Engineer role building data acquisition and munging pipelines. Requires strong Python3 (NumPy, Pandas), advanced SQL, scalable algorithm and data-structure implementation on distributed clusters, converting code to functional paradigms, and the ability to learn PySpark or Kafka quickly. Product-development, startup experience and real-world pipeline projects preferred.