AI/ML Engineer (2-5 Years Experience | Immediate Joiner | Remote)
YMinds.AI
AnywhereENTRY
RemoteMachine LearningData ScienceAI/ML
Job Description
Seeking an AI/ML Engineer to build intelligent decision systems.
Responsibilities
- Design, develop, and deploy production-grade machine learning systems
- Build recommendation systems, ranking models, and retrieval-based solutions
- Develop prediction, forecasting, clustering, anomaly detection, and optimization models
- Work with embeddings, similarity search, and representation learning techniques
- Build data processing pipelines and production-ready ML workflows
- Perform feature engineering, exploratory data analysis (EDA), and behavioral modeling
- Define evaluation frameworks and measure both model performance and business impact
- Translate business challenges into machine learning problems and identify meaningful signals in complex datasets
- Analyze model failures, optimize performance, and improve reliability
- Collaborate with product and engineering teams to deliver scalable, data-driven solutions
- Balance model quality, operational constraints, and business objectives when designing solutions
Qualifications
- 2–5 years of hands-on experience building production ML systems
- Experience shipping at least one machine learning-powered feature or workflow into production
- Strong understanding of supervised learning, feature engineering, and model evaluation
- Experience with recommendation systems, ranking systems, embeddings, and representation learning
- Knowledge of experimentation methodologies, model debugging, and performance analysis
- Strong understanding of offline and online model evaluation techniques
- Solid grasp of bias-variance tradeoffs, precision-recall tradeoffs, calibration, overfitting, and distribution shift concepts
- Strong programming skills in Python, Pandas, NumPy, and SQL
- Experience building data processing pipelines and working with production codebases
- Experience with APIs and data integrations
- Ability to work with real-world datasets and measure business impact
- Strong analytical thinking, problem-solving, and communication skills
Nice to have
- Experience with cloud platforms, distributed systems, orchestration frameworks, or MLOps tools
- Experience building recommendation, ranking, search, or retrieval systems
- Knowledge of forecasting, optimization, and experimentation frameworks
- Experience deploying ML systems into production environments
- Background in commerce, marketplace, SaaS, or consumer product domains
- Experience building data products with measurable business outcomes
- Familiarity with modern AI systems and hybrid ML/AI architectures
Benefits
- Professional growth
- Exciting challenges