Backend and AI/ML Engineer
2 weeks ago
Job Description
We are seeking a highly skilled and versatile
Backend and AI/ML Engineer
to join our team. In this role, you will design and develop scalable backend infrastructure and implement AI/ML solutions to power our platform. You will work on building robust APIs, integrating vector-based search engines, and deploying machine learning models to enhance the platform's intelligence and usability.
Responsibilities
- Design, develop, and maintain backend systems, services, and APIs to support platform functionality.
- Build and integrate scalable file processing pipelines for document ingestion, chunking, and metadata extraction.
- Develop and deploy machine learning models for semantic search, document embeddings, and summarization.
- Implement vector similarity search using tools like Milvus, FAISS, or Pinecone.
- Collaborate with cross-functional teams, including frontend developers and product managers, to deliver end-to-end solutions.
- Optimize the performance and scalability of backend and AI/ML systems.
- Ensure system security and implement authentication mechanisms such as OAuth and JWT.
- Research and experiment with the latest AI/ML approaches to improve platform intelligence and user experience.
- Monitor and improve the performance of deployed models, retraining as necessary.
- Document code, processes, and technical decisions to ensure maintainability.
Requirements
- Programming Skills
: Proficiency in
Python
and
. Familiarity with frameworks such as
Flask and Nodejs - Backend Knowledge
: Strong experience with RESTful APIs, microservices architecture, and database systems (e.g.,
MongoDB
). - AI/ML Expertise
: Hands-on experience with machine learning frameworks such as
TensorFlow
,
PyTorch
, or
Scikit-learn
. Proficiency in NLP tools like
Hugging Face
,
SpaCy
, or
NLTK
. - Vector Search
: Familiarity with vector databases like
Milvus
,
FAISS
for implementing semantic search. - Cloud and Deployment
: Experience with deploying backend and AI/ML solutions using cloud platforms (AWS, GCP, Azure) and containerization tools like
Docker
and
Kubernetes
. - Version Control and CI/CD
: Knowledge of tools like
Git
,
DVC
,
MLflow
, or
Kubeflow
for managing pipelines and deployment workflows. - Performance Optimization
: Skills in optimizing both backend services and AI/ML models for performance and scalability.
Preferred Skills
- Prior experience building AI-powered applications.
- Understanding of large language models (e.g., GPT, BERT) and their fine-tuning.
- Familiarity with secure coding practices and data privacy regulations.
- Knowledge of tools for managing machine learning workflows in production (
Apache Nifi,
Airflow
).
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