Lead Data Scientist + AIML
3 days ago
Job Title: AIML Engineer + Cloud (AWS, GCP & Azure)
Experience: 7+ Years
Employment Type: Full-time
Job Summary
We are looking for an experienced AI Engineer with deep expertise in designing, developing, and deploying AI/ML solutions on the AWS cloud platform. The ideal candidate should have hands-on experience in machine learning, deep learning, NLP, and MLOps, along with a strong understanding of AWS AI/ML services and end-to-end model lifecycle management.
Key Responsibilities
- Design, build, and deploy AI/ML models and pipelines using AWS services such as SageMaker, Lambda, Glue, and Step Functions.
- Collaborate with data scientists, data engineers, and cross-functional teams to translate business requirements into scalable AI solutions.
- Develop and optimize deep learning models for NLP, computer vision, recommendation systems, and predictive analytics.
- Implement data ingestion, transformation, and feature engineering pipelines leveraging AWS services (Glue, Redshift, S3, Athena).
- Handle the end-to-end ML lifecycle including experimentation, training, evaluation, deployment, and monitoring.
- Integrate AI models into production applications using REST APIs, containers, or microservices.
- Apply MLOps practices for automation, versioning, CI/CD, and model governance.
- Continuously explore and adopt new AI frameworks and AWS innovations to enhance solution capabilities.
Required Skills & Qualifications
- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related fields.
- 58 years of professional experience in AI/ML engineering or machine learning development.
- Strong proficiency in Python and related libraries (TensorFlow, PyTorch, scikit-learn, pandas, numpy).
Expertise in AWS AI/ML services including:
SageMaker, Comprehend, Rekognition, Transcribe, Textract, Polly
Lambda, Glue, ECR, ECS, Redshift, S3
Proven experience in building and deploying deep learning and NLP models.
- Solid understanding of software engineering principles including CI/CD, Git-based version control, and testing.
- Knowledge of containerization (Docker) and orchestration (Kubernetes, AWS ECS/EKS).
Preferred Skills
- Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker Pipelines.
- Familiarity with Generative AI models (LLMs, prompt engineering, embeddings, vector databases).
- Exposure to APIs, microservices, and serverless architectures.
- Experience with data visualization tools (QuickSight, Power BI, Tableau).
- Understanding of AWS security, monitoring, and cost optimization best practices
About ApexonApexon is a digital-first technology company helping businesses grow through innovation and smarter digital solutions. We work with clients at every step of their digital journey using tools like AI, data, cloud, apps, and user experience design to create powerful digital products. We focus on building #HumanFirstDigital experiences that put people at the center of technology. Diversity & Inclusion- Apexon is a Great Place to Work Certified company in the USA, India, and UK. We're proud of our inclusive culture where everyone is respected and empoweredregardless of race, gender, age, background, or identity. Visit- |
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