
Full Stack Developer with AI/ML Expertise
2 days ago
Location:
Onsite
Employment Type:
Full-time
Experience:
2+ years
Job Summary:
We are seeking a skilled and enthusiastic
Full Stack Developer
with hands-on experience in
AI/ML technologies
to join our engineering team. The ideal candidate should be proficient in both front-end and back-end development, and capable of designing, developing, and deploying AI-driven web applications.
This role requires a blend of software engineering expertise and practical experience in building or integrating AI/ML models into scalable applications.
Key Responsibilities:
- Design, develop, test, and maintain full-stack web applications.
- Collaborate with data scientists and ML engineers to integrate machine learning models into production environments.
- Build RESTful APIs or GraphQL services to expose AI capabilities.
- Develop intuitive front-end interfaces to visualize AI/ML results and data analytics.
- Optimize performance of applications, focusing on scalability, reliability, and security.
- Implement CI/CD pipelines and deployment processes using modern DevOps tools.
- Maintain documentation and ensure best practices in coding, testing, and deployment.
Required Skills & Qualifications:
Full Stack Development:
- Strong knowledge of
JavaScript/TypeScript
, with frameworks like
React
,
Angular
, or
. - Backend experience using
,
Python (Flask/Django/FastAPI)
,
Java
, or
.NET
. - Experience with
databases
: SQL (PostgreSQL/MySQL) and NoSQL (MongoDB, Firebase, etc.). - Knowledge of API development (RESTful & GraphQL).
- Version control using
Git
.
AI/ML:
- Experience with
Python
ML libraries:
scikit-learn
,
TensorFlow
,
Keras
,
PyTorch
, or
Hugging Face Transformers
. - Familiarity with
model training
,
fine-tuning
, and
inference pipelines
. - Understanding of ML lifecycle (data processing, training, evaluation, and deployment).
- Exposure to tools like
MLflow
,
Kubeflow
, or
TensorBoard
is a plus.
DevOps & Deployment:
- Experience with
Docker
,
Kubernetes
, or serverless functions. - Familiarity with cloud platforms like
AWS
,
GCP
, or
Azure
for deploying AI solutions.
Preferred Qualifications:
- Bachelor's or Master's in Computer Science, Data Science, or a related field.
- Prior experience working on
AI-driven products
, such as recommendation systems, chatbots, or predictive analytics tools. - Understanding of
MLOps
and AI model monitoring in production. - Knowledge of
LLMs (Large Language Models)
or
generative AI tools
is a strong plus.
Soft Skills:
- Strong analytical and problem-solving skills.
- Excellent communication and teamwork.
- Ability to manage multiple tasks and meet deadlines.
-
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