
Machine Learning Engineer
1 week ago
Role Description
We are seeking a
full-time Machine Learning Engineer
based in
India (remote)
to join our team. In this role, you will design, develop, and productionize scalable machine learning models that solve real-world problems. You will work across the full ML lifecycle, from data preprocessing and feature engineering to model training, deployment, and monitoring.
You will collaborate closely with data scientists, software engineers, and product managers to integrate ML solutions into production systems, ensuring robustness, scalability, and maintainability. This includes analyzing large and complex datasets, building automated pipelines, and optimizing algorithms for performance and efficiency.
You will also be responsible for keeping up-to-date with the latest advancements in ML/AI research and identifying opportunities to bring innovative approaches into our production systems.
Key Responsibilities
- Model Development & Deployment
: Design, train, and deploy machine learning models (e.g., deep neural networks, gradient boosting, time-series models) into production environments. - Data Engineering
: Build scalable pipelines for data ingestion, cleaning, feature extraction, and transformation. - Production Systems
: Implement CI/CD workflows, monitoring, and model retraining systems to ensure production stability. - Optimization & Performance
: Analyze algorithmic performance, optimize model efficiency, and reduce latency/cost in production workloads.
Qualifications
Technical Foundations
:
- Strong understanding of
neural networks
(CNNs, RNNs, Transformers) and their applications. - Solid knowledge of
computer science fundamentals
(algorithms, data structures, distributed systems). - Proficiency in
statistics, probability, and data analysis
for model evaluation and experimental design.
Hands-on Experience
:
- Proficiency with
Python
and machine learning libraries/frameworks such as
TensorFlow, PyTorch, Scikit-learn, XGBoost
. - Experience with
SQL/NoSQL databases
,
data warehouses
(e.g., BigQuery, Snowflake), and
data pipelines
(e.g., Airflow, Prefect, Spark). - Knowledge of
cloud ML platforms
(AWS Sagemaker, GCP Vertex AI, or Azure ML). - Familiarity with
MLOps tools
(MLflow, Kubeflow, Docker, Kubernetes). - Education
: - Bachelor's or Master's degree in
Computer Science, Artificial Intelligence, or a related field
.
Soft Skills
:
- Excellent
problem-solving and analytical skills
. - Strong
communication skills
to work effectively with both technical and non-technical stakeholders. - Ability to work in a
fast-paced, remote, and collaborative environment
.
Nice to Haves
:
- Prior experience in
sustainability-focused projects
(e.g., climate modeling, renewable energy optimization, carbon footprint analysis). - Contributions to
open-source ML/AI projects
.
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