Pipeline run
6e50736d-a1ed-4f83-aaa2-b785167559c3
Pipeline LLM cost (USD)
API 1: $0.0041
API 2: $0.0000
API 3: $0.0000
Total: $0.0041
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionNature of work
—
Tech stack maturity
Mainstream Modern
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
1.70 / 5
· Title match
✓ Has AI skill
✓ AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
—
Frameworks (×2):
—
Models / concepts (×3):
Machine Learning
Evidence — skills matched in JD (19)
C
C++
x86
ARM
SSE
AVX
NEON
AV1
H.265
Git
Machine Learning
Neural Networks
H.264
MPEG-2
VP9
OpenCL
CUDA
Multi-threading
Cache Optimization
Skill cluster (0 dimension groups, role-scoped)
Show KRA description ↓
The prospective candidate will be part of the Advanced Video and Research Team that designs and delivers video codec solutions for industry leaders in video technology.
The key responsibilities of the job would be to deliver and excel on the following fronts (not limited to):
• Development and implementation of optimized algorithms for video encoders, video decoders, video pre and post processing components on x86 and ARM based CPUs
• Work involves implementation of high quality video encoders, decoders and transcoders and associated intellectual properties like Motion estimation, Rate Control algorithms, Scene Cut Detection, Fade-in / Fade-out Compensation, De-interlacing, De-noising as an example
• Working on latest technology of Machine learning and Neural Network based video compression
• Knowledge of C/C++
• Knowledge of x86 based development, intrinsic like SSE, AVX based coding
• Knowledge of ARM based development, intrinsic like Neon coding
• Debugging, profiling and development environments
• Good knowledge of video standards like AV1 and H.265
• Working knowledge of H.264, MPEG-2 and VP9 is good to possess
• Software Processes, Git, Configuration Management, Test Planning and Execution
• Exposure to multi-threaded, cache optimal designs of video codecs
• Exposure to OpenCL based GPU development / CUDA based programming
• Aware of Machine learning and Neural Network basics.
Signals
Skill
ml-engineer
0.11
Alias
android-engineer
0.69
KRA
ml-engineer
0.31
Post-classification
Centroid—
Alias collision log—
New-role queue#44
New skills captured0
New KRA captured—
Status:
extract_from_jd_done
Created: 2026-05-20T11:33:56.288688Z
Updated: 2026-05-20T11:33:56.931173Z
Flow
Current 3-step pipeline
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Role
Chosen role & resolution
No chosen role stored for this run.
Job description
Role : Video Codec Engineer Required Experience: Candidates must have development experience ranging from 2 to 4 years. • Experience in implementing video compression standards based and/or proprietary Image and Video codecs/algorithms • Must have exposure and development experience ARM and/or x86 based platforms like Xeon E5/E3, Core-i7/i5 • Experience of development using operating systems like Windows / Linux / OS X Job Description: The prospective candidate will be part of the Advanced Video and Research Team that designs and delivers video codec solutions for industry leaders in video technology. Responsibility: The key responsibilities of the job would be to deliver and excel on the following fronts (not limited to): • Development and implementation of optimized algorithms for video encoders, video decoders, video pre and post processing components on x86 and ARM based CPUs • Work involves implementation of high quality video encoders, decoders and transcoders and associated intellectual properties like Motion estimation, Rate Control algorithms, Scene Cut Detection, Fade-in / Fade-out Compensation, De-interlacing, De-noising as an example • Working on latest technology of Machine learning and Neural Network based video compression Educational Qualification: Masters or Bachelor’s Degree in Computer Science / Electronics and Communication Required Technical Skills: • Knowledge of C/C++ • Knowledge of x86 based development, intrinsic like SSE, AVX based coding • Knowledge of ARM based development, intrinsic like Neon coding • Debugging, profiling and development environments • Good knowledge of video standards like AV1 and H.265 • Working knowledge of H.264, MPEG-2 and VP9 is good to possess • Software Processes, Git, Configuration Management, Test Planning and Execution • Exposure to multi-threaded, cache optimal designs of video codecs • Exposure to OpenCL based GPU development / CUDA based programming • Aware of Machine learning and Neural Network basics. Location: Bengaluru, Karnataka
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
C
Primary
No API 2 row (run stopped after API 1 or history missing)
C++
Primary
No API 2 row (run stopped after API 1 or history missing)
x86
Primary
No API 2 row (run stopped after API 1 or history missing)
ARM
Primary
No API 2 row (run stopped after API 1 or history missing)
SSE
Primary
No API 2 row (run stopped after API 1 or history missing)
AVX
Primary
No API 2 row (run stopped after API 1 or history missing)
NEON
Primary
No API 2 row (run stopped after API 1 or history missing)
AV1
Primary
No API 2 row (run stopped after API 1 or history missing)
H.265
Primary
No API 2 row (run stopped after API 1 or history missing)
H.264
Secondary
No API 2 row (run stopped after API 1 or history missing)
MPEG-2
Secondary
No API 2 row (run stopped after API 1 or history missing)
VP9
Secondary
No API 2 row (run stopped after API 1 or history missing)
Git
Primary
No API 2 row (run stopped after API 1 or history missing)
OpenCL
Secondary
No API 2 row (run stopped after API 1 or history missing)
CUDA
Secondary
No API 2 row (run stopped after API 1 or history missing)
Machine Learning
Primary
No API 2 row (run stopped after API 1 or history missing)
Neural Networks
Primary
No API 2 row (run stopped after API 1 or history missing)
Multi-threading
Secondary
No API 2 row (run stopped after API 1 or history missing)
Cache Optimization
Secondary
No API 2 row (run stopped after API 1 or history missing)
Library artifacts (this run)
No artifact rows for this run.
nano JD Parser — gpt-4.1-nano click to toggle
RoleVideo Codec Engineer
ExperienceCandidates must have development experience ranging from 2 to 4 years.
DomainOther
Location
Bengaluru, India
JD type
pass
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "Other"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE - Computer Science / Electronics and Communication",
"raw": "Masters or Bachelor\u2019s Degree in Computer Science / Electronics and Communication",
"requirement": "required"
}
],
"experience": {
"max": 4,
"min": 2,
"raw": "Candidates must have development experience ranging from 2 to 4 years."
},
"job_locations": [
{
"aliases": [
"Bangalore"
],
"city": "Bengaluru",
"country": "India",
"state": "Karnataka",
"work_mode": null
}
],
"role": "Video Codec Engineer",
"role_aliases": [
"Codec Engineer",
"Video Engineer",
"Software Engineer"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Job Description",
"heading_was_present": true,
"source_marker": {
"first_5_words": "The prospective candidate will be",
"last_5_words": "in video technology."
},
"text": "The prospective candidate will be part of the Advanced Video and Research Team that designs and delivers video codec solutions for industry leaders in video technology.",
"word_count": 27
},
{
"bullet_count": 3,
"heading": "Responsibility",
"heading_was_present": true,
"source_marker": {
"first_5_words": "The key responsibilities of the",
"last_5_words": "video compression"
},
"text": "The key responsibilities of the job would be to deliver and excel on the following fronts (not limited to):\n\u2022 Development and implementation of optimized algorithms for video encoders, video decoders, video pre and post processing components on x86 and ARM based CPUs\n\u2022 Work involves implementation of high quality video encoders, decoders and transcoders and associated intellectual properties like Motion estimation, Rate Control algorithms, Scene Cut Detection, Fade-in / Fade-out Compensation, De-interlacing, De-noising as an example\n\u2022 Working on latest technology of Machine learning and Neural Network based video compression",
"word_count": 64
},
{
"bullet_count": 10,
"heading": "Required Technical Skills",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Knowledge of C/C++\n\u2022 Knowledge of",
"last_5_words": "and Neural Network basics."
},
"text": "\u2022 Knowledge of C/C++\n\u2022 Knowledge of x86 based development, intrinsic like SSE, AVX based coding\n\u2022 Knowledge of ARM based development, intrinsic like Neon coding\n\u2022 Debugging, profiling and development environments\n\u2022 Good knowledge of video standards like AV1 and H.265\n\u2022 Working knowledge of H.264, MPEG-2 and VP9 is good to possess\n\u2022 Software Processes, Git, Configuration Management, Test Planning and Execution\n\u2022 Exposure to multi-threaded, cache optimal designs of video codecs\n\u2022 Exposure to OpenCL based GPU development / CUDA based programming\n\u2022 Aware of Machine learning and Neural Network basics.",
"word_count": 104
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "C"
},
{
"is_primary": true,
"skill_name": "C++"
},
{
"is_primary": true,
"skill_name": "x86"
},
{
"is_primary": true,
"skill_name": "ARM"
},
{
"is_primary": true,
"skill_name": "SSE"
},
{
"is_primary": true,
"skill_name": "AVX"
},
{
"is_primary": true,
"skill_name": "NEON"
},
{
"is_primary": true,
"skill_name": "AV1"
},
{
"is_primary": true,
"skill_name": "H.265"
},
{
"is_primary": false,
"skill_name": "H.264"
},
{
"is_primary": false,
"skill_name": "MPEG-2"
},
{
"is_primary": false,
"skill_name": "VP9"
},
{
"is_primary": true,
"skill_name": "Git"
},
{
"is_primary": false,
"skill_name": "OpenCL"
},
{
"is_primary": false,
"skill_name": "CUDA"
},
{
"is_primary": true,
"skill_name": "Machine Learning"
},
{
"is_primary": true,
"skill_name": "Neural Networks"
},
{
"is_primary": false,
"skill_name": "Multi-threading"
},
{
"is_primary": false,
"skill_name": "Cache Optimization"
}
],
"jd_role": {
"display_name": "Video Codec Engineer",
"rationale": null,
"role_aliases": [
"Codec Engineer",
"Video Engineer",
"Software Engineer"
],
"role_archetype": "Engineering",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "Other"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE - Computer Science / Electronics and Communication",
"raw": "Masters or Bachelor\u2019s Degree in Computer Science / Electronics and Communication",
"requirement": "required"
}
],
"experience": {
"max": 4,
"min": 2,
"raw": "Candidates must have development experience ranging from 2 to 4 years."
},
"job_locations": [
{
"aliases": [
"Bangalore"
],
"city": "Bengaluru",
"country": "India",
"state": "Karnataka",
"work_mode": null
}
],
"role": "Video Codec Engineer",
"role_aliases": [
"Codec Engineer",
"Video Engineer",
"Software Engineer"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Job Description",
"heading_was_present": true,
"source_marker": {
"first_5_words": "The prospective candidate will be",
"last_5_words": "in video technology."
},
"text": "The prospective candidate will be part of the Advanced Video and Research Team that designs and delivers video codec solutions for industry leaders in video technology.",
"word_count": 27
},
{
"bullet_count": 3,
"heading": "Responsibility",
"heading_was_present": true,
"source_marker": {
"first_5_words": "The key responsibilities of the",
"last_5_words": "video compression"
},
"text": "The key responsibilities of the job would be to deliver and excel on the following fronts (not limited to):\n\u2022 Development and implementation of optimized algorithms for video encoders, video decoders, video pre and post processing components on x86 and ARM based CPUs\n\u2022 Work involves implementation of high quality video encoders, decoders and transcoders and associated intellectual properties like Motion estimation, Rate Control algorithms, Scene Cut Detection, Fade-in / Fade-out Compensation, De-interlacing, De-noising as an example\n\u2022 Working on latest technology of Machine learning and Neural Network based video compression",
"word_count": 64
},
{
"bullet_count": 10,
"heading": "Required Technical Skills",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Knowledge of C/C++\n\u2022 Knowledge of",
"last_5_words": "and Neural Network basics."
},
"text": "\u2022 Knowledge of C/C++\n\u2022 Knowledge of x86 based development, intrinsic like SSE, AVX based coding\n\u2022 Knowledge of ARM based development, intrinsic like Neon coding\n\u2022 Debugging, profiling and development environments\n\u2022 Good knowledge of video standards like AV1 and H.265\n\u2022 Working knowledge of H.264, MPEG-2 and VP9 is good to possess\n\u2022 Software Processes, Git, Configuration Management, Test Planning and Execution\n\u2022 Exposure to multi-threaded, cache optimal designs of video codecs\n\u2022 Exposure to OpenCL based GPU development / CUDA based programming\n\u2022 Aware of Machine learning and Neural Network basics.",
"word_count": 104
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "6e50736d-a1ed-4f83-aaa2-b785167559c3",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
"display_name": "Android Engineer",
"matched_count": null,
"role_id": 4,
"score": 0.6923,
"slug": "android-engineer",
"total_count": null
},
{
"display_name": "Backend Engineer",
"matched_count": null,
"role_id": 1,
"score": 0.6923,
"slug": "backend-engineer",
"total_count": null
},
{
"display_name": "AR/VR Engineer",
"matched_count": null,
"role_id": 8,
"score": 0.5882,
"slug": "ar-vr-engineer",
"total_count": null
},
{
"display_name": "ML Engineer",
"matched_count": null,
"role_id": 3,
"score": 0.5294,
"slug": "ml-engineer",
"total_count": null
},
{
"display_name": "Frontend Engineer",
"matched_count": null,
"role_id": 7,
"score": 0.5,
"slug": "frontend-engineer",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "ML Engineer",
"matched_count": null,
"role_id": 3,
"score": 0.314,
"slug": "ml-engineer",
"total_count": null
},
{
"display_name": "DevOps Engineer",
"matched_count": null,
"role_id": 10,
"score": 0.3086,
"slug": "devops-engineer",
"total_count": null
},
{
"display_name": "Data Engineer",
"matched_count": null,
"role_id": 2,
"score": 0.3079,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "Hybrid Mobile Developer",
"matched_count": null,
"role_id": 11,
"score": 0.2872,
"slug": "hybrid-mobile-developer",
"total_count": null
},
{
"display_name": "Full Stack Engineer",
"matched_count": null,
"role_id": 15,
"score": 0.2785,
"slug": "full-stack-engineer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "ML Engineer",
"matched_count": 2,
"role_id": 3,
"score": 0.1053,
"slug": "ml-engineer",
"total_count": 19
},
{
"display_name": "ML Ops Engineer",
"matched_count": 2,
"role_id": 16,
"score": 0.1053,
"slug": "ml-ops-engineer",
"total_count": 19
},
{
"display_name": "Backend Engineer",
"matched_count": 1,
"role_id": 1,
"score": 0.0526,
"slug": "backend-engineer",
"total_count": 19
},
{
"display_name": "AI Engineer",
"matched_count": 1,
"role_id": 13,
"score": 0.0526,
"slug": "ai-engineer",
"total_count": 19
},
{
"display_name": "Full Stack Engineer",
"matched_count": 1,
"role_id": 15,
"score": 0.0526,
"slug": "full-stack-engineer",
"total_count": 19
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "E",
"chosen_role": null,
"confidence": 0.0,
"llm2_fired": false,
"llm2_reasoning": null,
"queued": true,
"reasoning": "low_kra: top KRA 0.31 \u003c 0.4"
},
"stage5_updates": {
"centroid_n_after": null,
"centroid_updated": false,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [],
"queue_entry_id": 44,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{}
API 3 — final-role-output
{}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.
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