Sr. AI/ML Developer

Job Title: AI/ML Engineer

Location: Alpharetta, GA (In-Person Interview required)

Experience: 6–10+ years

Employment Type: Full-time

Role Summary

We are looking for an experienced AI/ML Engineer to design, develop, deploy, and scale advanced machine learning and AI-driven solutions. The ideal candidate should have strong hands-on experience with Python, deep learning frameworks, LLMs, data pipelines, and cloud technologies.

Key Responsibilities

* Design and build end‑to‑end ML pipelines for training, validation, deployment, and monitoring.

* Develop and optimize ML models including supervised, unsupervised, and deep learning algorithms.

* Work with LLMs, embeddings, vector databases, and retrieval‑augmented generation (RAG) systems.

* Implement model evaluation, experimentation (A/B testing), and performance tuning.

* Collaborate with data engineering teams to build scalable data ingestion and preprocessing pipelines.

* Develop APIs/microservices for deploying ML models into production environments.

* Apply MLOps practices (CI/CD, automation, feature store, model registry, monitoring).

* Integrate AI models with cloud platforms (AWS/GCP/Azure).

* Research and implement new AI techniques, tools, frameworks, and best practices.

* Work closely with product, engineering, and business stakeholders to translate requirements into AI solutions.

Required Skills

* Strong programming skills in Python.

* Hands-on experience with ML/DL frameworks:

* TensorFlow, PyTorch, Keras, Scikit‑Learn.

* Solid understanding of:

* Machine Learning, Deep Learning, NLP, LLMs, Transformers.

* Experience building RAG applications, prompt engineering, and using LLM APIs (OpenAI, Anthropic, Azure OpenAI).

* Proficiency with data processing tools:

* Pandas, NumPy, Spark (optional).

* Experience with vector databases (FAISS, Pinecone, Chroma, Weaviate).

* Good understanding of MLOps tools:

* MLflow, Kubeflow, Airflow, Docker, Kubernetes.

* Cloud platform hands‑on (AWS/GCP/Azure).

* Strong understanding of algorithms, data structures, model evaluation, and production‑grade coding.

Good to Have

* Experience building agentic AI systems or autonomous agents.

* Knowledge of LangChain, LlamaIndex, Haystack.

* Experience with Kafka, event streaming, or real-time inference.

* Familiarity with microservices (FastAPI / Flask).

* Exposure to security, data governance, and responsible AI.

* Domain knowledge (FinTech, BFSI, Healthcare, Retail, etc.).

Education

* Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.