AI ML Engineer
AI ML Engineer
anthrobyte.ai- Posted 2 months ago
- Over 200 applicants have applied
Job Description
We're looking for a passionate and driven AI Engineer to join our fast-growing startup. You'll work at the intersection of AI research and product engineering — building intelligent systems that solve real business problems. If you get excited by cutting-edge models, thrive in a collaborative culture, and love turning ideas into working products, this role is for you.
Requirements
Requirements
- Design, develop, and deploy AI/ML models for production use cases
- Translate ambiguous business problems into concrete AI-driven solutions
- Collaborate cross-functionally with product, data, and business teams
- Build and maintain data pipelines, model training, and inference systems
- Continuously experiment, iterate, and improve model performance
- Contribute to the team's technical culture through code reviews and knowledge sharing
- 1–2 years of hands-on AI/ML experience
- Proficiency in Python (NumPy, Pandas, Scikit-learn)
- Experience with ML frameworks — TensorFlow or PyTorch
- Understanding of NLP, computer vision, or generative AI
- Familiarity with REST APIs and model deployment
- Strong fundamentals in statistics & algorithms
- Git & version control practices
- Experience with LLMs and prompt engineering
- Cloud platforms (AWS, GCP, Azure)
- MLOps tools (MLflow, DVC, Weights & Biases)
- Docker / Kubernetes basics
- SQL and data wrangling skills
- Exposure to FastAPI or Flask for model serving.
- Preferred: Participation in Kaggle competitions (ranked / medallist) or hackathons strongly preferred. It shows initiative, problem-solving ability, and a passion for continuous learning — qualities we deeply value.
More Info
Key Skills
Weights Biases
Generative AI
Scikit-learn
MLflow
DVC
Model Deployment
About Company
Skills:
Tensorflow, Python, Machine Learning Algorithms, data preprocessing, R-Studio, feature engineering, cloud platforms and services
Skills:
Machine Learning, Nlp, Docker, Bash, Python, Deep Learning, MLops, Salesforce, GCP Professional Cloud Architect, CI/CD tools, ML pipelines, Gemini, Model training, GPT-4, Large Language Models, AI governance and ethics
Skills:
Sql, Tensorflow, Azure ML, Nlp, MLops, Azure Functions, Pytorch, Elasticsearch, Rest Apis, Azure, Ocr, Python, Computer Vision, AWS, LiteDB, Document Intelligence, ML deployment practices, annotation tooling, ADLS, ML engineering
Skills:
Python Programming, metrics, evaluation datasets, fine-tuning, LLM and AI fundamentals, Analytical Skills, AI agent architecture, prompt optimization, production ML AI systems, structured testing, benchmarks, model and LLM evaluation, root-cause analysis, model improvement