Lead RL Environment Engineer
Adzzat
- Pay
- ₹15–20 lakh a year
- Location
- Mumbai, India · On-site
- Job type
- Full-time
- RL environment construction
- ML fundamentals
- RL fundamentals
- gradient descent
- Python
- Linux
- Docker
- deployment
A d z z a t i s a n a p p l i e d A I r e s e a r c h l a b t h a t t u r n s e n t e r p r i s e d a t a a n d h u m a n e x p e r t i s e i n t o t r a i n i n g
d a t a a n d e v a l u a t i o n s f o r f r o n t i e r A I l a b s .
L o c a t i o n: M u m b a i , I n d i a .
L e a d R L E n v i r o n m e n t E n g i n e e r
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1 5 - 2 0 L P A + E S O P s
L e a d t h e d e s i g n a n d d e l i v e r y o f R L e n v i r o n m e n t s b u i l t f r o m s u p p l i e d c o d e a n d d o m a i n d a t a .
A n e n d - t o - e n d , M L - l e a n i n g b u i l d e r r o l e , n o t a p u r e b a c k e n d o r r e s e a r c h - o n l y r o l e .
What you'll do
D e c i d e w h i c h d a t a c a n b e c o m e a u s e f u l e n v i r o n m e n t a n d c l a r i f y w h a t d a t a a l a b n e e d s .
W o r k b a c k w a r d s f r o m e x i s t i n g b e n c h m a r k s , o r d e s i g n s u i t a b l e e v a l u a t i o n s .
B u i l d r e w a r d s , g r a d e r s a n d v e r i f i e r s t h a t s c o r e a g e n t r u n s a n d r e s i s t s h o r t c u t s a n d r e w a r d
h a c k i n g .
R u n a g e n t e x p e r i m e n t s a n d m e a s u r e w h e t h e r p o s t - t r a i n i n g i m p r o v e s p e r f o r m a n c e .
S h i p c o n t a i n e r i s e d , r e p r o d u c i b l e s e t u p s i n D o c k e r , i n a s t a n d a r d f o r m a t s u c h a s H a r b o r .
Non-negotiable
Y o u h a v e p e r s o n a l l y b u i l t a t l e a s t o n e R L e n v i r o n m e n t . S h o w a r u n n a b l e r e p o o r i n s p e c t a b l e
a r t i f a c t a n d e x p l a i n w h a t y o u b u i l t .
Strong skills
M L a n d R L f u n d a m e n t a l s ( i n c l u d i n g g r a d i e n t d e s c e n t a n d h o w R L e n v i r o n m e n t s w o r k ) ; s t r o n g
r e c e n t P y t h o n ; L i n u x , D o c k e r , d e p l o y m e n t a n d s a n d b o x e s ; v e r i f i e r d e s i g n t h a t r e s i s t s g a m i n g .
T r a i n i n g o r p o s t - t r a i n i n g m o d e l s i s a s t r o n g e x t r a s i g n a l .
a d z z a t l a b s . c o m
What you’ll do
- Lead the design and delivery of RL environments built from supplied code and domain data
- Decide which data can become a useful environment and clarify what data a lab needs
- Work backwards from existing benchmarks, or design suitable evaluations
- Build rewards, graders and verifiers that score agent runs and resist shortcuts and reward hacking
- Run agent experiments and measure whether post-training improves performance
- Ship containerised, reproducible setups in Docker, in a standard format such as Harbor
What we’re looking for
Must have
- RL environment construction
- ML fundamentals
- RL fundamentals
- gradient descent
- Python
- Linux
Nice to have
- model training
- post-training models