AI/ML Software Developer
2 weeks ago
We are seeking a skilled
AI/ML Software Developer
to design, develop, and deploy intelligent systems and machine learning models that solve real-world problems. You'll work closely with software engineers, and product teams to integrate ML models into scalable production systems.
Key Responsibilities
Design & Development
Build and optimize end-to-end machine learning pipelines (data ingestion → model training → inference → monitoring).
Implement ML/DL algorithms using frameworks such as
TensorFlow, PyTorch, or Scikit-learn
.Develop APIs, microservices, and backend systems to serve ML models in production (e.g.,
FastAPI, Flask, or gRPC
).
Model Lifecycle Management
Perform data preprocessing, feature engineering, and model validation.
Optimize models for
inference latency, accuracy, and resource efficiency
.Deploy models using
Docker, Kubernetes, or AWS/GCP/Azure ML services
is a plus.
Research & Innovation
Experiment with emerging techniques (e.g.,
transformers, RAG, generative AI, reinforcement learning
) and integrate into products.Collaborate on building
custom LLM applications
using frameworks like
LangChain, LlamaIndex, or Hugging Face
.
Testing & Monitoring
- Implement CI/CD pipelines for ML models.
- Monitor drift, performance metrics, and retraining triggers.
Required Skills
- Strong programming skills in
Python
. - Proficiency in ML/DL frameworks:
TensorFlow, PyTorch, Scikit-learn
. - Experience with
data handling
(NumPy, Pandas, SQL, Spark). - Understanding of
MLOps
tools: MLflow, Kubeflow, Airflow, or DVC is a plus. - Familiarity with
cloud services
(AWS Sagemaker, GCP Vertex AI, or Azure ML) is a plus. - Solid grasp of
algorithms, statistics, and optimization techniques
. - Strong software engineering principles - version control (Git), unit testing, and clean code practices.
Preferred Qualifications
- Experience with
LLMs, RAG pipelines, or Generative AI (OpenAI, Anthropic, etc.)
. - Knowledge of
vector databases
(FAISS, Pinecone, Weaviate). - Exposure to
DevOps and containerization
(Docker, Kubernetes) is a plus. - Background in
NLP or Time-Series Forecasting
is a plus.
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