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Senior Machine Learning Engineer

2 weeks ago

Lahore, Punjab, Pakistan Kavtech Solutions (Private) Ltd. Full time 2,000,000 - 2,500,000 per year

Company Overview:

Kavtech Solutions (Pvt) Limited is a leading Data & AI company, recognized for its expertise in Data Visualization, Data Warehousing, Data Integration, Business Intelligence, and Machine Learning/Artificial Intelligence. With a strong portfolio of partnerships and development contracts with global clients, Kavtech Solutions is at the forefront of delivering innovative and data-driven solutions across various industries.

About the Role

We are seeking an experienced
AI/ML Architect
to design and lead enterprise-scale AI and ML solutions on AWS. The ideal candidate will have strong expertise in
Amazon SageMaker
for traditional ML pipelines and
Amazon Bedrock
for Generative AI use cases. This role requires technical leadership, solution architecture, and the ability to collaborate with business stakeholders, data engineers, and ML teams to deliver scalable, secure, and cost-efficient AI/ML systems.

Key Responsibilities

  • Architect and design
    end-to-end ML and GenAI solutions
    using AWS services (SageMaker, Bedrock, Lambda, Step Functions, Glue, Redshift, S3).
  • Define and implement
    ML pipelines
    covering data ingestion, preprocessing, training, hyperparameter tuning, deployment, and monitoring.
  • Leverage
    Amazon Bedrock
    to design and deploy Generative AI solutions such as chatbots, copilots, RAG (retrieval-augmented generation) systems, and content generation tools.
  • Select appropriate
    foundation models (Claude, Llama, Titan, etc.)
    and fine-tune/integrate them with enterprise data.
  • Ensure solutions are
    secure, scalable, and cost-optimized
    , following AWS Well-Architected Framework.
  • Collaborate with stakeholders to gather requirements and translate them into
    architectural blueprints and technical roadmaps
    .
  • Provide
    technical leadership and mentorship
    to ML engineers, data scientists, and developers.
  • Establish
    best practices
    for model governance, monitoring, versioning, and CI/CD of ML workloads.
  • Stay updated with emerging
    AI/ML technologies, AWS services, and industry trends
    to drive innovation.

Required Skills & Qualifications

  • Bachelor's or Master's degree in Computer Science, AI/ML, Data Engineering, or related field.
  • 8+ years of professional experience in
    data engineering, ML engineering, or AI solution architecture
    .
  • Proven expertise in
    AWS SageMaker
    (training, deployment, pipelines, feature store, monitoring).
  • Strong experience with
    Amazon Bedrock
    and building
    GenAI applications
    .
  • Hands-on skills in
    Python, PyTorch/TensorFlow, and SQL
    .
  • Solid understanding of
    LLMs, prompt engineering, RAG, and fine-tuning techniques
    .
  • Experience with
    data pipelines and integration
    (Glue, Redshift, Athena, EMR).
  • Familiarity with
    DevOps/MLOps practices
    (CI/CD, IaC with Terraform/CloudFormation, model registry, monitoring).
  • Strong knowledge of
    security, IAM, encryption, and compliance in cloud environments
    .
  • Excellent
    leadership, communication, and stakeholder management
    skills.

Preferred Skills (Nice-to-Have)

  • AWS Certified Machine Learning – Specialty
    or
    AWS Certified Solutions Architect – Professional
    .
  • Experience with
    LangChain, Vector Databases (Pinecone, Weaviate, FAISS), or Knowledge Graphs
    .
  • Exposure to
    streaming platforms
    (Kafka, Kinesis) and
    real-time ML systems
    .
  • Knowledge of
    MLOps platforms
    (MLflow, Kubeflow, etc.).

Perks and Benefits:

  • Competitive salary accompanied by an attractive benefits package.
  • Paid annual leaves to promote work-life balance.
  • Health insurance (OPD & IPD)
  • Free lunch and gym allowance to support a healthy lifestyle.
  • Yearly performance-based increments to recognize your hard work.
  • Learning allowance to facilitate your professional growth.
  • Participation in company-sponsored events to foster a vibrant work culture.