About the role
Our client is seeking a highly motivatedAI/ML Engineer (24 years)with hands-on experience in developing machine learning models, building data pipelines, and integrating ML solutions into production systems. You will collaborate with engineering, data, and product teams to deliver intelligent, scalable AI solutions across multiple domains.
This role is ideal for someone who has strong foundational ML knowledge, exposure to deep learning/LLMs, and is ready to work on end-to-end ML lifecycle projects
Key Responsibilities
- Develop, train, and optimize machine learning and deep learning models for real-world applications.
- Build, maintain, and improve ML pipelines including data preprocessing, feature engineering, and model deployment.
- Implement ML algorithms using Python, scikit-learn, TensorFlow, PyTorch, or related frameworks.
- Work with large datasets to design efficient ETL workflows and ensure training data quality.
- Deploy ML models into production using APIs, microservices, or cloud-native services.
- Participate in model evaluation, A/B testing, drift monitoring, and continuous performance improvements.
- Collaborate with engineering teams to integrate ML models within existing systems.
- Stay updated with recent research, tools, and best practices in ML, DL, NLP, and LLMs.
- Write clean, maintainable code following engineering best practices.
Required Skills
- 24 years of hands-on experience in Machine Learning or applied AI development.
- Strong proficiency inPythonand ML libraries (scikit-learn, NumPy, Pandas).
- Solid understanding of supervised & unsupervised learning algorithms.
- Experience with frameworks such asTensorFloworPyTorch.
- Basic exposure toNLPorLLM-based modelsis preferred.
- Knowledge of building and deploying model pipelines.
- Familiarity with data pipelines, ETL processes, and handling structured/unstructured data.
- Experience working with APIs, microservices, or ML model deployment workflows.
- Good understanding of Git, version control, and collaborative coding.
Preferred Skills (Good to Have)
- Experience with cloud ML platforms (AWS Sagemaker, Azure ML, GCP Vertex AI).
- Basic understanding of vector databases and retrieval systems.
- Exposure to MLOps tools: MLflow, Kubeflow, Airflow, or DVC.
- Experience with Docker and containerized deployments.
- Familiarity with LLM fine-tuning, embeddings, or RAG pipelines.
- Hands-on experience with SQL/NoSQL databases.
Soft skill
- Strong analytical and problem-solving abilities.
- Ability to break down ambiguous problems into structured ML tasks.
- Good communication skills for cross-functional collaboration.
- Curiosity and willingness to learn new technologies.
- Team player with a proactive attitude.
Must have skills
- Strong proficiency in Python and ML libraries (NumPy, Pandas, scikit-learn)
- Solid understanding of machine learning algorithms, feature engineering, and model evaluation
- Hands-on experience with deep learning frameworks (PyTorch or TensorFlow)
- Experience in data preprocessing, working with large datasets, and SQL
- Ability to build, deploy, and serve ML models using REST APIs (FastAPI/Flask)
- Working knowledge of Docker and basic cloud platforms (AWS/GCP/Azure)
- Familiarity with MLOps practices (model versioning, experiment tracking, monitoring)
- Proficiency with Git and collaborative development workflows
- Strong problem-solving, communication, and documentation skills
AboutYMinds.AI
YMinds.AIis a premier talent solutions company specializing in identifying and placing top-tier engineering and technology leaders with high-growth startups and global enterprises. We partner closely with our clients to deliver senior, high-impact talent that drives architectural excellence, innovation, scalability, and long-term business success.
Hashtags
#AIMLEngineer #MachineLearningEngineer #MachineLearning #DeepLearning #NLP #LLM #TensorFlow #PyTorch #ScikitLearn #DataEngineering #MLOps #AIEngineer #PythonDeveloper #ArtificialIntelligence #AIJobs #TechHiring
Required Skills
Machine Learning: Very Important
Python: Very Important
TensorFlow: Very Important
PyTorch: Very Important
Data Engineering: Important
Natural Language Processing (NLP): Important
ETL Processes: Important
APIs (REST, GraphQL): Important
Docker: Important
MLOps: Important
SQL: Important
Git: Important
Qualifications
[Some qualifications you may want to include are Skills, Education, Experience, or Certifications.]
Example: Excellent verbal and written communication skills
