.. : Communication: L. Required Skillset: Configuration Management: System Administration: Strong expertise in Linux/Windows system Administration. Networking: Basic .. Engineering Practices: CI/CD Pipelines: Tool and Infrastructure Development: Monitoring and Alerting: Production Systems: Automation: Incident Management: .. read more
Software Engineer - AI Models & Vector Database
We are seeking a highly skilled
Software Engineer
with a passion for developing cutting-edge AI solutions. In this role, you will be at the forefront of innovation, working with
Small Language Models (SLMs), Large Language Models (LLMs), Vision Models,
and
Retrieval-Augmented Generation (RAG)
systems. You'll have the opportunity to work on projects that integrate advanced AI capabilities with
vector databases
to deliver high-performance, scalable solutions.
Key Responsibilities: AI Model Development & Optimization : Design, implement, and optimize both
small
and
large-scale language models
(SLMs & LLMs) tailored for diverse applications such as NLP, question-answering, text generation, and summarization. Vision Models : Collaborate with cross-functional teams to integrate
computer vision
models into multi-modal AI systems, enabling seamless interaction between text and visual inputs. Retrieval-Augmented Generation (RAG) : Build and refine
RAG architectures
to improve information retrieval in AI systems, enhancing the model’s ability to generate accurate and contextually relevant responses from large data sets. Vector Database Integration : Leverage
vector databases
for high-speed retrieval and semantic search capabilities, ensuring efficient storage, indexing, and querying of high-dimensional data. Model Fine-Tuning & Deployment : Work on the fine-tuning and deployment of models into production environments, ensuring they are optimized for performance and scalability. Collaboration : Partner with research scientists, data engineers, and product teams to translate complex AI research into production-ready software.
Required Skills: Strong programming skills in
Python, TensorFlow, PyTorch,
Jupyter , or similar. Experience with
LLMs
like GPT, BERT, or similar models, as well as familiarity with
SLMs . Knowledge of
Vision Models
such as CNNs, R-CNNs, or ViTs (Vision Transformers). Proficiency in
RAG
techniques, combining language models with efficient retrieval mechanisms. Hands-on experience working with
vector databases . Familiarity with cloud platforms and containerization. Strong problem-solving skills and ability to work in a collaborative, fast-paced environment.
Preferred Qualifications: Previous experience working on large-scale AI systems or building multi-modal AI applications. Familiarity with state-of-the-art
NLP
and
computer vision
research. Experience in
ML Ops
practices and deployment pipelines for AI models.
Join our team to work on some of the most exciting challenges in AI, leveraging the latest advancements in LLMs, vision models, RAG systems, and vector databases to create next-generation solutions!
Take a look at our Website, follow us on GitHub, and jump in our Discord to say hello.
GitHub:
https://github.com/swarmauri Discord:
https://discord.gg/nBKuZ36x9Q Website:
https://swarmauri.com
We are seeking a highly skilled
Software Engineer
with a passion for developing cutting-edge AI solutions. In this role, you will be at the forefront of innovation, working with
Small Language Models (SLMs), Large Language Models (LLMs), Vision Models,
and
Retrieval-Augmented Generation (RAG)
systems. You'll have the opportunity to work on projects that integrate advanced AI capabilities with
vector databases
to deliver high-performance, scalable solutions.
Key Responsibilities: AI Model Development & Optimization : Design, implement, and optimize both
small
and
large-scale language models
(SLMs & LLMs) tailored for diverse applications such as NLP, question-answering, text generation, and summarization. Vision Models : Collaborate with cross-functional teams to integrate
computer vision
models into multi-modal AI systems, enabling seamless interaction between text and visual inputs. Retrieval-Augmented Generation (RAG) : Build and refine
RAG architectures
to improve information retrieval in AI systems, enhancing the model’s ability to generate accurate and contextually relevant responses from large data sets. Vector Database Integration : Leverage
vector databases
for high-speed retrieval and semantic search capabilities, ensuring efficient storage, indexing, and querying of high-dimensional data. Model Fine-Tuning & Deployment : Work on the fine-tuning and deployment of models into production environments, ensuring they are optimized for performance and scalability. Collaboration : Partner with research scientists, data engineers, and product teams to translate complex AI research into production-ready software.
Required Skills: Strong programming skills in
Python, TensorFlow, PyTorch,
Jupyter , or similar. Experience with
LLMs
like GPT, BERT, or similar models, as well as familiarity with
SLMs . Knowledge of
Vision Models
such as CNNs, R-CNNs, or ViTs (Vision Transformers). Proficiency in
RAG
techniques, combining language models with efficient retrieval mechanisms. Hands-on experience working with
vector databases . Familiarity with cloud platforms and containerization. Strong problem-solving skills and ability to work in a collaborative, fast-paced environment.
Preferred Qualifications: Previous experience working on large-scale AI systems or building multi-modal AI applications. Familiarity with state-of-the-art
NLP
and
computer vision
research. Experience in
ML Ops
practices and deployment pipelines for AI models.
Join our team to work on some of the most exciting challenges in AI, leveraging the latest advancements in LLMs, vision models, RAG systems, and vector databases to create next-generation solutions!
Take a look at our Website, follow us on GitHub, and jump in our Discord to say hello.
GitHub:
https://github.com/swarmauri Discord:
https://discord.gg/nBKuZ36x9Q Website:
https://swarmauri.com