Machine Learning Engineer
- For Career Direction
- Work From Home
- 2 to 6 Years
Key Responsibilities
- Develop, train, and improve machine learning models for real-world applications
- Handle and preprocess large datasets using SQL and Python
- Perform model engineering to improve accuracy, performance, and scalability
- Deploy machine learning models into production environments
- Monitor model performance and support continuous improvement
- Collaborate with data, engineering, and product teams across use cases
Must-Have Skills
- Strong proficiency in Python and ML libraries (scikit-learn, XGBoost, Keras)
- Expert-level data handling using SQL for efficient querying, transformation, & analysis of large datasets.
- Experience with feature engineering, feature selection, and model optimization
- Hands-on exposure to model deployment and productionization
- Understanding of ML workflows, pipelines, and evaluation metrics
- Good problem-solving and communication skills
Good to Have
- Exposure to Deep Learning or NLP use cases
- Experience with ML pipelines, CI/CD, or MLOps tools
- Familiarity with cloud platforms (AWS, Azure, GCP)
- Knowledge of model monitoring, drift detection, and retraining strategies
- Experience working in hybrid or agile environments
- Interest in certifications or upskilling in AI/ML technologies
About the job
Here, opportunities come in two ways — roles within Career Direction and roles for our client requirements. Most internal positions are Work From Home, providing flexibility, comfort, and a balanced work environment. Client-based roles may require Hybrid or Work From Office setups depending on project demands, collaboration needs, and company policies. This structure allows candidates to explore a wide range of opportunities and apply for roles that best align with their skills, preferences, and long-term career goals.
Career Direction benefits apply only to Career Direction employees and may include health and wellness support, financial wellbeing programs, flexibility and time off, family care assistance, community involvement opportunities, and personal development support. These benefits, along with growth opportunities, are provided based on factors such as performance, dedication, skill level, assessment results, and available projects. Offerings may vary as they depend on organizational policies, project requirements, and client expectations.
Note: Salary range information is omitted as it applies to US-based roles, and compensation details will be discussed during the interview.
