CareerXperts Consulting
Website:
careerxperts.com
Job details:
We’re looking for a Machine Learning Engineer who operates at the intersection of data, engineering, and business outcomes. This role is not just about building models—it’s about deploying reliable, scalable ML systems that solve real-world problems and drive measurable impact.
You’ll work closely with data scientists, product managers, and engineering teams to take models from experimentation to production—ensuring they perform, scale, and evolve with the business.
Key Responsibilities
- Design, build, and deploy scalable machine learning models into production environments
- Translate business problems into ML solutions with clear success metrics
- Develop and maintain end-to-end ML pipelines (data ingestion → training → deployment → monitoring)
- Optimize model performance, latency, and cost efficiency in production systems
- Work on feature engineering, model selection, and hyperparameter tuning
- Implement model monitoring, drift detection, and continuous retraining strategies
- Collaborate with data engineering teams to ensure clean, reliable, and accessible data
- Ensure ML systems follow best practices in versioning, testing, and reproducibility
- Contribute to architecture decisions for ML platforms and infrastructure
Required Skills & Experience
- Strong programming skills in Python
- Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Solid understanding of supervised and unsupervised learning techniques
- Experience building and deploying models using REST APIs or microservices
- Familiarity with data processing tools (Pandas, NumPy, Spark)
- Experience with cloud platforms like Amazon Web Services, Google Cloud Platform, or Microsoft Azure
- Understanding of CI/CD pipelines and containerization (Docker, Kubernetes)
- Strong grasp of software engineering fundamentals (testing, version control, system design)
Good to Have
- Experience with MLOps tools (MLflow, Kubeflow, SageMaker)
- Exposure to deep learning, NLP, or computer vision use cases
- Experience working with large-scale distributed systems
- Knowledge of data warehousing and big data ecosystems
Click on Apply to know more.