diff --git a/.github/workflows/test-slurm-jobs.yml b/.github/workflows/test-slurm-jobs.yml
new file mode 100644
index 0000000..78efeeb
--- /dev/null
+++ b/.github/workflows/test-slurm-jobs.yml
@@ -0,0 +1,127 @@
+name: Test SLURM Jobs
+
+on:
+  push:
+    branches: [ main, develop ]
+    paths:
+      - 'scripts/job_*.sh'
+      - 'research/**/job_*.sh'
+      - 'docker/slurm/**'
+      - '.github/workflows/test-slurm-jobs.yml'
+  pull_request:
+    branches: [ main, develop ]
+    paths:
+      - 'scripts/job_*.sh'
+      - 'research/**/job_*.sh'
+      - 'docker/slurm/**'
+      - '.github/workflows/test-slurm-jobs.yml'
+  workflow_dispatch:
+
+jobs:
+  test-slurm-environment:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+    
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+      
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+      
+      - name: Build SLURM Docker images
+        run: |
+          docker-compose -f docker-compose.slurm.yml build
+      
+      - name: Start SLURM cluster
+        run: |
+          docker-compose -f docker-compose.slurm.yml up -d
+          # Wait for SLURM to be ready
+          sleep 30
+      
+      - name: Check SLURM cluster status
+        run: |
+          docker exec ami-ml-slurmctld sinfo
+          docker exec ami-ml-slurmctld scontrol show nodes
+      
+      - name: Test basic SLURM job submission
+        run: |
+          # Submit test job
+          docker exec ami-ml-slurmctld bash -c "cd /workspace && sbatch docker/slurm/examples/job_hello.sh"
+          
+          # Wait for job to complete
+          sleep 10
+          
+          # Check job status
+          docker exec ami-ml-slurmctld squeue
+          
+          # Display job output
+          docker exec ami-ml-slurmctld bash -c "cd /workspace && cat hello_slurm_*.out || echo 'Job output not found yet'"
+      
+      - name: Test environment setup job
+        run: |
+          # Submit environment test job (simplified version that doesn't require network)
+          docker exec ami-ml-slurmctld bash -c "cd /workspace && cat > /tmp/test_simple.sh << 'EOF'
+#!/bin/bash
+#SBATCH --job-name=test_simple
+#SBATCH --output=test_simple_%j.out
+#SBATCH --ntasks=1
+#SBATCH --time=00:05:00
+#SBATCH --mem=2G
+#SBATCH --cpus-per-task=1
+#SBATCH --partition=main
+
+echo \"Testing basic environment...\"
+echo \"Job ID: \$SLURM_JOB_ID\"
+echo \"Working directory: \$(pwd)\"
+echo \"Python version:\"
+python3 --version
+echo \"Conda available:\"
+which conda
+conda --version
+echo \"Poetry available:\"
+which poetry || echo \"Poetry not in PATH\"
+poetry --version || echo \"Poetry command failed\"
+echo \"Workspace contents:\"
+ls -la /workspace/ | head -20
+echo \"Test completed successfully!\"
+EOF
+"
+          docker exec ami-ml-slurmctld chmod +x /tmp/test_simple.sh
+          
+          JOB_ID=$(docker exec ami-ml-slurmctld bash -c "sbatch /tmp/test_simple.sh" | grep -oP '\d+')
+          echo "Submitted job ID: $JOB_ID"
+          
+          # Wait for job to complete (with timeout)
+          timeout=60
+          elapsed=0
+          while [ $elapsed -lt $timeout ]; do
+            status=$(docker exec ami-ml-slurmctld squeue -j $JOB_ID -h -o "%T" 2>/dev/null || echo "COMPLETED")
+            if [ "$status" = "COMPLETED" ] || [ -z "$status" ]; then
+              echo "Job $JOB_ID completed"
+              break
+            fi
+            echo "Job $JOB_ID status: $status (waiting...)"
+            sleep 5
+            elapsed=$((elapsed + 5))
+          done
+          
+          # Display job output
+          docker exec ami-ml-slurmctld bash -c "cd /workspace && cat test_simple_*.out"
+      
+      - name: Collect SLURM logs on failure
+        if: failure()
+        run: |
+          echo "=== SLURM Controller Logs ==="
+          docker-compose -f docker-compose.slurm.yml logs slurm-controller
+          echo "=== SLURM Compute Node Logs ==="
+          docker-compose -f docker-compose.slurm.yml logs slurm-compute
+          echo "=== All job outputs ==="
+          docker exec ami-ml-slurmctld bash -c "cd /workspace && ls -la *.out 2>/dev/null || echo 'No job outputs found'"
+          docker exec ami-ml-slurmctld bash -c "cd /workspace && cat *.out 2>/dev/null || echo 'No job outputs to display'"
+      
+      - name: Stop SLURM cluster
+        if: always()
+        run: |
+          docker-compose -f docker-compose.slurm.yml down -v
diff --git a/README.md b/README.md
index 504ddaf..d6a8e72 100644
--- a/README.md
+++ b/README.md
@@ -58,3 +58,27 @@ Alternatively, one can run the scripts without activating poetry's shell:
 ```bash
  poetry run python <script>
 ```
+
+## Testing SLURM Jobs Locally
+
+A Docker Compose environment is available for testing SLURM job scripts locally before submitting to DRAC/Compute Canada HPC clusters. This simulates a minimal SLURM environment with a controller and compute node.
+
+See [docker/slurm/README.md](docker/slurm/README.md) for detailed instructions on:
+- Starting the SLURM environment
+- Submitting and monitoring jobs
+- Adapting real job scripts for local testing
+- Troubleshooting common issues
+
+Quick start:
+```bash
+# Build and start the SLURM cluster
+docker-compose -f docker-compose.slurm.yml up -d
+
+# Access the controller to submit jobs
+docker exec -it ami-ml-slurmctld bash
+
+# Inside the container
+sinfo  # Check cluster status
+sbatch docker/slurm/examples/job_hello.sh  # Submit a test job
+squeue  # Check job queue
+```
diff --git a/docker-compose.slurm.yml b/docker-compose.slurm.yml
new file mode 100644
index 0000000..e667321
--- /dev/null
+++ b/docker-compose.slurm.yml
@@ -0,0 +1,61 @@
+services:
+  slurm-controller:
+    build:
+      context: .
+      dockerfile: docker/slurm/Dockerfile
+    image: ami-ml-slurm:latest
+    hostname: slurmctld
+    container_name: ami-ml-slurmctld
+    privileged: true
+    networks:
+      - slurm
+    volumes:
+      - ./:/workspace
+      - slurm-etc:/etc/slurm
+      - slurm-var:/var/spool/slurm
+      - slurm-log:/var/log/slurm
+    environment:
+      - SLURM_ROLE=controller
+    command: ["slurmctld"]
+    ports:
+      - "6817:6817"
+      - "6818:6818"
+
+  slurm-compute:
+    build:
+      context: .
+      dockerfile: docker/slurm/Dockerfile
+    image: ami-ml-slurm:latest
+    hostname: c1
+    container_name: ami-ml-c1
+    privileged: true
+    networks:
+      - slurm
+    volumes:
+      - ./:/workspace
+      - slurm-etc:/etc/slurm
+      - slurm-var:/var/spool/slurm
+      - slurm-log:/var/log/slurm
+    environment:
+      - SLURM_ROLE=compute
+    command: ["slurmd"]
+    depends_on:
+      - slurm-controller
+    # Uncomment the deploy section below to enable GPU support
+    # Requires NVIDIA Docker runtime to be installed
+    # deploy:
+    #   resources:
+    #     reservations:
+    #       devices:
+    #         - driver: nvidia
+    #           count: all
+    #           capabilities: [gpu]
+
+networks:
+  slurm:
+    driver: bridge
+
+volumes:
+  slurm-etc:
+  slurm-var:
+  slurm-log:
diff --git a/docker/slurm/Dockerfile b/docker/slurm/Dockerfile
new file mode 100644
index 0000000..fdeda47
--- /dev/null
+++ b/docker/slurm/Dockerfile
@@ -0,0 +1,60 @@
+FROM ubuntu:22.04
+
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Install basic dependencies and SLURM from Ubuntu packages
+RUN apt-get update && apt-get install -y \
+    wget \
+    curl \
+    gcc \
+    make \
+    build-essential \
+    munge \
+    slurm-wlm \
+    slurm-wlm-basic-plugins \
+    slurmd \
+    slurmctld \
+    python3 \
+    python3-pip \
+    python3-dev \
+    git \
+    vim \
+    sudo \
+    supervisor \
+    && rm -rf /var/lib/apt/lists/*
+
+# Create required directories
+RUN mkdir -p /var/spool/slurm/ctld \
+    /var/spool/slurm/d \
+    /var/log/slurm \
+    /etc/slurm \
+    /run/munge
+
+# Install Miniconda
+RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh && \
+    bash /tmp/miniconda.sh -b -p /opt/miniconda3 && \
+    rm /tmp/miniconda.sh
+
+ENV PATH="/opt/miniconda3/bin:${PATH}"
+
+# Install Poetry
+RUN pip3 install poetry
+
+# Copy SLURM configuration files
+COPY docker/slurm/slurm.conf /etc/slurm/slurm.conf
+COPY docker/slurm/cgroup.conf /etc/slurm/cgroup.conf
+# COPY docker/slurm/gres.conf /etc/slurm/gres.conf  # Uncomment for GPU support
+
+# Set proper permissions
+RUN chown -R slurm:slurm /var/spool/slurm /var/log/slurm && \
+    chown -R munge:munge /etc/munge /var/log/munge /run/munge && \
+    chmod 700 /etc/munge /var/log/munge /run/munge
+
+# Copy entrypoint script
+COPY docker/slurm/entrypoint.sh /usr/local/bin/entrypoint.sh
+RUN chmod +x /usr/local/bin/entrypoint.sh
+
+WORKDIR /workspace
+
+ENTRYPOINT ["/usr/local/bin/entrypoint.sh"]
+CMD ["slurmctld"]
diff --git a/docker/slurm/README.md b/docker/slurm/README.md
new file mode 100644
index 0000000..4c6d9ed
--- /dev/null
+++ b/docker/slurm/README.md
@@ -0,0 +1,345 @@
+# SLURM Docker Environment for Local Testing
+
+This directory contains a Docker Compose setup that simulates a SLURM environment for local testing of job scripts before submitting to DRAC/Compute Canada HPC clusters.
+
+## Overview
+
+The environment consists of:
+- **SLURM Controller** (`slurmctld`): Manages job scheduling and cluster state
+- **Compute Node** (`c1`): Single compute node with 4 CPUs, 16GB RAM, and optional GPU support
+- **Partitions**: Configured to match DRAC's partition structure:
+  - `main`: Default partition for general compute jobs (max 48h)
+  - `long`: For longer-running jobs (unlimited time)
+  - `long-cpu`: CPU-only jobs with unlimited time
+
+## Configuration
+
+The SLURM configuration is based on [DRAC/Compute Canada documentation](https://docs.alliancecan.ca/wiki/Running_jobs) and matches the behavior of their clusters as closely as possible:
+
+- **Authentication**: MUNGE for inter-process communication
+- **Scheduling**: Backfill scheduler with fair-share policies
+- **Resource Management**: Cgroup-based process tracking and resource constraints
+- **GPU Support**: Optional GPU passthrough using NVIDIA Docker runtime
+
+## Prerequisites
+
+1. **Docker** and **Docker Compose** installed
+2. **NVIDIA Docker** (optional, for GPU support):
+   ```bash
+   # Install NVIDIA Container Toolkit
+   distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
+   curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
+   curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | \
+     sudo tee /etc/apt/sources.list.d/nvidia-docker.list
+   sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
+   sudo systemctl restart docker
+   ```
+
+## Quick Start
+
+### 1. Build and Start the Environment
+
+```bash
+# From the repository root
+docker-compose -f docker-compose.slurm.yml build
+docker-compose -f docker-compose.slurm.yml up -d
+```
+
+Wait for both containers to start (approximately 30 seconds):
+
+```bash
+# Check container status
+docker-compose -f docker-compose.slurm.yml ps
+
+# View logs
+docker-compose -f docker-compose.slurm.yml logs -f
+```
+
+### 2. Access the SLURM Controller
+
+```bash
+# Enter the controller container
+docker exec -it ami-ml-slurmctld bash
+```
+
+### 3. Check SLURM Status
+
+```bash
+# Check cluster info
+sinfo
+
+# Check node status
+scontrol show nodes
+
+# Check partition configuration
+scontrol show partitions
+```
+
+Expected output from `sinfo`:
+```
+PARTITION AVAIL  TIMELIMIT  NODES  STATE NODELIST
+main*        up 2-00:00:00      1   idle c1
+long         up   infinite      1   idle c1
+long-cpu     up   infinite      1   idle c1
+```
+
+### 4. Submit a Test Job
+
+```bash
+# Inside the controller container, navigate to workspace
+cd /workspace
+
+# Submit a simple test job
+sbatch docker/slurm/examples/job_hello.sh
+
+# Check job status
+squeue
+
+# View job output (after completion)
+cat hello_slurm_*.out
+```
+
+### 5. Test with Real Job Scripts
+
+The repository's job scripts can be tested by copying and modifying them:
+
+```bash
+# Example: Test the training classifier job
+# Note: You may need to adjust paths and reduce epochs for quick testing
+
+# Copy an existing job script
+cp research/order_level_classifier/job_train_classifier.sh docker/slurm/examples/job_test_quick.sh
+
+# Edit to reduce runtime (e.g., fewer epochs, smaller dataset)
+# Then submit
+sbatch docker/slurm/examples/job_test_quick.sh
+```
+
+## Testing Workflow
+
+### Environment Setup Test
+
+Test that the conda environment and Poetry work correctly:
+
+```bash
+sbatch docker/slurm/examples/job_test_env.sh
+squeue  # Check job status
+cat test_env_setup_*.out  # View output after completion
+```
+
+### AMI-ML Package Test
+
+Test that the ami-ml commands are available:
+
+```bash
+sbatch docker/slurm/examples/job_test_ami_ml.sh
+```
+
+## Common SLURM Commands
+
+### Job Management
+
+```bash
+# Submit a job
+sbatch job_script.sh
+
+# Check job queue
+squeue
+squeue -u $USER  # Your jobs only
+
+# Get detailed job info
+scontrol show job <job_id>
+
+# Cancel a job
+scancel <job_id>
+
+# View completed job info
+sacct -j <job_id>
+```
+
+### Node and Partition Info
+
+```bash
+# List partitions
+sinfo -s
+
+# Show detailed partition info
+scontrol show partition main
+
+# Show node details
+scontrol show node c1
+```
+
+### Resource Monitoring
+
+```bash
+# Monitor job output in real-time
+tail -f <output_file>.out
+
+# Check cluster load
+sinfo -N -l
+```
+
+## Testing GPU Jobs
+
+If you have NVIDIA GPUs and the NVIDIA Docker runtime installed:
+
+```bash
+# Submit a GPU job
+sbatch --gres=gpu:1 docker/slurm/examples/job_gpu_test.sh
+
+# Check GPU availability
+scontrol show node c1 | grep Gres
+```
+
+To test without GPU (CPU-only smoke tests):
+- Remove or comment out the `#SBATCH --gres=gpu:*` line
+- Reduce training to 1-2 epochs
+- Use smaller batch sizes
+
+## Adapting Real Job Scripts
+
+When adapting real job scripts from `research/` or `scripts/`:
+
+1. **Module Loading**: The container uses conda directly, not `module load`
+   ```bash
+   # Real SLURM:
+   module load miniconda/3
+   conda activate ami-ml
+   
+   # Docker SLURM:
+   eval "$(/opt/miniconda3/bin/conda shell.bash hook)"
+   conda activate ami-ml
+   ```
+
+2. **Data Paths**: Use paths relative to `/workspace` (project root)
+   ```bash
+   # Real SLURM (uses environment variables):
+   --train_webdataset $ORDER_WBDS_ALL
+   
+   # Docker SLURM (use local paths or set env vars):
+   --train_webdataset /workspace/data/train_*.tar
+   ```
+
+3. **Temporary Storage**: `$SLURM_TMPDIR` works the same way in the container
+
+4. **Resource Requests**: Adjust to fit the container limits (4 CPUs, 16GB RAM, optional GPU support)
+
+## Troubleshooting
+
+### SLURM Controller Not Starting
+
+```bash
+# Check controller logs
+docker-compose -f docker-compose.slurm.yml logs slurm-controller
+
+# Common issues:
+# - Munge key not generated properly
+# - Configuration file errors
+
+# Restart the environment
+docker-compose -f docker-compose.slurm.yml down -v
+docker-compose -f docker-compose.slurm.yml up -d
+```
+
+### Jobs Stuck in Pending State
+
+```bash
+# Check why job is pending
+scontrol show job <job_id>
+
+# Common reasons:
+# - Requested resources exceed node capacity
+# - Wrong partition name
+# - Compute node not responding
+
+# Check node state
+scontrol show node c1
+
+# If node is down, set it to idle
+scontrol update nodename=c1 state=idle
+```
+
+### Permission Issues
+
+```bash
+# Ensure workspace is accessible
+ls -la /workspace
+
+# Check SLURM user permissions
+id slurm
+```
+
+### Conda Environment Issues
+
+```bash
+# If conda environment doesn't exist, create it:
+conda create -n ami-ml python=3.9 -y
+conda activate ami-ml
+cd /workspace
+poetry install
+```
+
+## Stopping the Environment
+
+```bash
+# Stop containers
+docker-compose -f docker-compose.slurm.yml down
+
+# Stop and remove volumes (clean state)
+docker-compose -f docker-compose.slurm.yml down -v
+```
+
+## Advanced Configuration
+
+### Customizing Node Resources
+
+Edit `docker/slurm/slurm.conf` to adjust resources:
+
+```conf
+NodeName=c1 CPUs=16 RealMemory=64000 Gres=gpu:4 State=UNKNOWN
+```
+
+Then rebuild:
+```bash
+docker-compose -f docker-compose.slurm.yml build
+docker-compose -f docker-compose.slurm.yml up -d
+```
+
+### Adding More Compute Nodes
+
+Edit `docker-compose.slurm.yml` to add more nodes, and update `slurm.conf` accordingly.
+
+### Persistent Storage
+
+Job outputs and SLURM logs are stored in Docker volumes. To use host directories instead:
+
+```yaml
+volumes:
+  - ./slurm-logs:/var/log/slurm
+  - ./slurm-spool:/var/spool/slurm
+```
+
+## Differences from Real DRAC SLURM
+
+1. **Scale**: Single node vs. multi-node cluster
+2. **Modules**: No `module load` environment modules (uses conda directly)
+3. **Storage**: No scratch/project filesystem hierarchy
+4. **Accounting**: No database accounting (uses flat file)
+5. **Network**: No high-speed interconnect (InfiniBand)
+
+Despite these differences, the job script syntax, resource allocation, and scheduling behavior closely match DRAC's environment.
+
+## CI/CD Integration
+
+This SLURM environment can be used in GitHub Actions for automated testing. See `.github/workflows/test-slurm-jobs.yml` for an example workflow.
+
+## Resources
+
+- [DRAC Running Jobs Documentation](https://docs.alliancecan.ca/wiki/Running_jobs)
+- [SLURM Documentation](https://slurm.schedmd.com/)
+- [SLURM Docker Cluster](https://github.com/giovtorres/slurm-docker-cluster)
+
+## Support
+
+For issues with the Docker SLURM environment, please open an issue in the repository.
diff --git a/docker/slurm/cgroup.conf b/docker/slurm/cgroup.conf
new file mode 100644
index 0000000..38b34b4
--- /dev/null
+++ b/docker/slurm/cgroup.conf
@@ -0,0 +1,11 @@
+###
+# SLURM cgroup configuration
+###
+
+CgroupAutomount=yes
+CgroupReleaseAgentDir="/etc/slurm/cgroup"
+
+ConstrainCores=yes
+ConstrainRAMSpace=yes
+ConstrainSwapSpace=yes
+ConstrainDevices=yes
diff --git a/docker/slurm/entrypoint.sh b/docker/slurm/entrypoint.sh
new file mode 100644
index 0000000..b33d15f
--- /dev/null
+++ b/docker/slurm/entrypoint.sh
@@ -0,0 +1,52 @@
+#!/bin/bash
+
+set -e
+
+# Generate munge key if it doesn't exist
+if [ ! -f /etc/munge/munge.key ]; then
+    echo "Generating munge key..."
+    dd if=/dev/urandom of=/etc/munge/munge.key bs=1 count=1024
+    chown munge:munge /etc/munge/munge.key
+    chmod 400 /etc/munge/munge.key
+fi
+
+# Ensure proper permissions
+chown -R munge:munge /etc/munge /var/log/munge /run/munge
+chown -R slurm:slurm /var/spool/slurm /var/log/slurm
+
+# Start munge
+echo "Starting munge..."
+sudo -u munge /usr/sbin/munged --force
+
+# Wait for munge to start
+sleep 2
+
+# Check what role this container should play
+ROLE=${SLURM_ROLE:-controller}
+
+if [ "$ROLE" = "controller" ]; then
+    echo "Starting SLURM controller (slurmctld)..."
+    
+    # Create state directory if it doesn't exist
+    mkdir -p /var/spool/slurm/ctld
+    chown slurm:slurm /var/spool/slurm/ctld
+    
+    # Start slurmctld
+    exec /usr/sbin/slurmctld -D -vvv
+    
+elif [ "$ROLE" = "compute" ]; then
+    echo "Starting SLURM compute node (slurmd)..."
+    
+    # Wait for controller to be ready
+    sleep 5
+    
+    # Create spool directory if it doesn't exist
+    mkdir -p /var/spool/slurm/d
+    chown slurm:slurm /var/spool/slurm/d
+    
+    # Start slurmd
+    exec /usr/sbin/slurmd -D -vvv
+else
+    echo "Unknown SLURM_ROLE: $ROLE"
+    exit 1
+fi
diff --git a/docker/slurm/examples/job_gpu_test.sh b/docker/slurm/examples/job_gpu_test.sh
new file mode 100644
index 0000000..f992333
--- /dev/null
+++ b/docker/slurm/examples/job_gpu_test.sh
@@ -0,0 +1,47 @@
+#!/bin/bash
+#SBATCH --job-name=gpu_test
+#SBATCH --output=gpu_test_%j.out
+#SBATCH --ntasks=1
+#SBATCH --time=00:05:00
+#SBATCH --mem=4G
+#SBATCH --cpus-per-task=2
+#SBATCH --gres=gpu:1
+#SBATCH --partition=main
+
+# Test job to verify GPU availability
+echo "Testing GPU availability..."
+echo "Job ID: $SLURM_JOB_ID"
+echo "GPUs allocated: $CUDA_VISIBLE_DEVICES"
+
+# Check for nvidia-smi
+if command -v nvidia-smi &> /dev/null; then
+    echo "nvidia-smi found, checking GPUs..."
+    nvidia-smi
+else
+    echo "nvidia-smi not found - GPU passthrough may not be configured"
+fi
+
+# Test PyTorch GPU availability
+cd /workspace
+eval "$(/opt/miniconda3/bin/conda shell.bash hook)"
+conda activate ami-ml 2>/dev/null || echo "ami-ml environment not found"
+
+python3 << EOF
+import sys
+try:
+    import torch
+    print(f"PyTorch version: {torch.__version__}")
+    print(f"CUDA available: {torch.cuda.is_available()}")
+    if torch.cuda.is_available():
+        print(f"CUDA version: {torch.version.cuda}")
+        print(f"Number of GPUs: {torch.cuda.device_count()}")
+        for i in range(torch.cuda.device_count()):
+            print(f"GPU {i}: {torch.cuda.get_device_name(i)}")
+    else:
+        print("No CUDA GPUs available")
+except ImportError:
+    print("PyTorch not installed")
+    sys.exit(0)
+EOF
+
+echo "GPU test completed!"
diff --git a/docker/slurm/examples/job_hello.sh b/docker/slurm/examples/job_hello.sh
new file mode 100644
index 0000000..1558e1d
--- /dev/null
+++ b/docker/slurm/examples/job_hello.sh
@@ -0,0 +1,20 @@
+#!/bin/bash
+#SBATCH --job-name=hello_slurm
+#SBATCH --output=hello_slurm_%j.out
+#SBATCH --ntasks=1
+#SBATCH --time=00:01:00
+#SBATCH --mem=1G
+#SBATCH --cpus-per-task=1
+#SBATCH --partition=main
+
+# Simple test job to verify SLURM is working
+echo "Hello from SLURM!"
+echo "Job ID: $SLURM_JOB_ID"
+echo "Node: $SLURM_NODELIST"
+echo "CPUs: $SLURM_CPUS_PER_TASK"
+echo "Memory: $SLURM_MEM_PER_NODE MB"
+echo "Working directory: $(pwd)"
+echo "Python version:"
+python3 --version
+echo "Conda version:"
+conda --version || echo "Conda not in PATH"
diff --git a/docker/slurm/examples/job_test_ami_ml.sh b/docker/slurm/examples/job_test_ami_ml.sh
new file mode 100644
index 0000000..87b1b0c
--- /dev/null
+++ b/docker/slurm/examples/job_test_ami_ml.sh
@@ -0,0 +1,43 @@
+#!/bin/bash
+#SBATCH --job-name=test_ami_ml_training
+#SBATCH --output=test_ami_ml_training_%j.out
+#SBATCH --ntasks=1
+#SBATCH --time=00:30:00
+#SBATCH --mem=8G
+#SBATCH --cpus-per-task=2
+#SBATCH --partition=main
+
+# Minimal training test to verify ami-ml package works
+echo "Testing ami-ml training setup..."
+echo "Job ID: $SLURM_JOB_ID"
+
+# Set working directory
+cd /workspace
+
+# Load conda and activate environment
+eval "$(/opt/miniconda3/bin/conda shell.bash hook)"
+conda activate ami-ml || {
+    echo "Creating ami-ml environment..."
+    conda create -n ami-ml python=3.9 -y
+    conda activate ami-ml
+    
+    # Install dependencies with Poetry
+    poetry install
+}
+
+# Load environment variables
+if [ -f .env ]; then
+    set -o allexport
+    source .env
+    set +o allexport
+    echo "Loaded environment variables from .env"
+else
+    echo "Warning: .env file not found"
+fi
+
+# Test that ami-ml commands are available
+echo "Testing ami-ml commands..."
+ami-classification --help || echo "ami-classification command not available"
+ami-dataset --help || echo "ami-dataset command not available"
+
+echo "Test completed successfully!"
diff --git a/docker/slurm/examples/job_test_env.sh b/docker/slurm/examples/job_test_env.sh
new file mode 100644
index 0000000..569c71c
--- /dev/null
+++ b/docker/slurm/examples/job_test_env.sh
@@ -0,0 +1,36 @@
+#!/bin/bash
+#SBATCH --job-name=test_env_setup
+#SBATCH --output=test_env_setup_%j.out
+#SBATCH --ntasks=1
+#SBATCH --time=00:10:00
+#SBATCH --mem=4G
+#SBATCH --cpus-per-task=2
+#SBATCH --partition=main
+
+# Test job to verify environment setup similar to real SLURM jobs
+echo "Testing environment setup..."
+echo "Job ID: $SLURM_JOB_ID"
+echo "Working directory: $(pwd)"
+
+# Check if we can load conda
+echo "Checking conda..."
+conda --version
+
+# Create and activate a test environment
+echo "Creating test conda environment..."
+conda create -n test-env python=3.9 -y
+conda activate test-env
+
+echo "Python in conda env:"
+which python
+python --version
+
+# Test if Poetry is available
+echo "Testing Poetry..."
+poetry --version || echo "Poetry not available in PATH"
+
+# Check if workspace is mounted
+echo "Checking workspace files..."
+ls -la /workspace/
+
+echo "Environment test completed successfully!"
diff --git a/docker/slurm/gres.conf b/docker/slurm/gres.conf
new file mode 100644
index 0000000..861c177
--- /dev/null
+++ b/docker/slurm/gres.conf
@@ -0,0 +1,2 @@
+NodeName=c1 Name=gpu File=/dev/nvidia0
+NodeName=c1 Name=gpu File=/dev/nvidia1
diff --git a/docker/slurm/slurm.conf b/docker/slurm/slurm.conf
new file mode 100644
index 0000000..6735ef3
--- /dev/null
+++ b/docker/slurm/slurm.conf
@@ -0,0 +1,78 @@
+# SLURM configuration for local testing
+# Based on DRAC/Compute Canada configuration
+# See: https://docs.alliancecan.ca/wiki/Running_jobs
+
+ClusterName=ami-ml-local
+SlurmctldHost=slurmctld
+
+# Authentication
+AuthType=auth/munge
+CryptoType=crypto/munge
+
+# Logging and accounting
+SlurmctldLogFile=/var/log/slurm/slurmctld.log
+SlurmdLogFile=/var/log/slurm/slurmd.log
+SlurmctldPidFile=/var/run/slurmctld.pid
+SlurmdPidFile=/var/run/slurmd.pid
+SlurmdSpoolDir=/var/spool/slurm/d
+StateSaveLocation=/var/spool/slurm/ctld
+
+# Process tracking (using pgid instead of cgroup for Docker compatibility)
+ProctrackType=proctrack/pgid
+# TaskPlugin=task/cgroup  # Commented out for Docker compatibility
+
+# Scheduling
+SchedulerType=sched/backfill
+SelectType=select/cons_tres
+SelectTypeParameters=CR_Core_Memory
+
+# Timers
+SlurmctldTimeout=300
+SlurmdTimeout=300
+InactiveLimit=0
+MinJobAge=300
+KillWait=30
+Waittime=0
+
+# Job submission
+MaxJobCount=10000
+MaxArraySize=1001
+
+# Resource limits
+# Match DRAC's approach to resource management
+DefMemPerCPU=256
+MaxMemPerCPU=0
+
+# Fair share scheduling
+PriorityType=priority/multifactor
+PriorityDecayHalfLife=7-0
+PriorityMaxAge=7-0
+PriorityWeightAge=1000
+PriorityWeightFairshare=10000
+PriorityWeightJobSize=1000
+PriorityWeightPartition=1000
+PriorityWeightQOS=0
+
+# Accounting
+AccountingStorageType=accounting_storage/none
+JobAcctGatherType=jobacct_gather/linux
+JobAcctGatherFrequency=30
+
+# Compute node configuration
+# Single node with multiple CPUs and optional GPU
+# For GPU support, uncomment Gres parameter and ensure gres.conf is configured
+NodeName=c1 CPUs=4 RealMemory=15994 State=UNKNOWN
+
+# Partition definitions (similar to DRAC partitions)
+# main partition (default, similar to DRAC's compute)
+PartitionName=main Nodes=c1 Default=YES MaxTime=48:00:00 State=UP
+
+# long partition (for longer jobs, similar to DRAC's long partition)
+PartitionName=long Nodes=c1 Default=NO MaxTime=INFINITE State=UP
+
+# long-cpu partition (CPU only, similar to DRAC)
+PartitionName=long-cpu Nodes=c1 Default=NO MaxTime=INFINITE State=UP
+
+# GPU resource configuration
+# Uncomment line below to enable GPU support
+# GresTypes=gpu